From 4552d3f9c8c0410bd5a1776f3639b0656542424e Mon Sep 17 00:00:00 2001 From: Vedansh Date: Mon, 27 Jan 2025 00:14:14 +0530 Subject: [PATCH] refractor: improve data analyst roadmap (#8104) * refractor 36 topics * refractor remaining topics - 16 --- ...laysis--reporting-with-excel@sgXIjVTbwdwdYoaxN3XBM.md | 2 ++ .../data-analyst/content/apis@4DFcXSSHxg5wv0uXLIRij.md | 2 +- .../content/average@yn1sstYMO9du3rpfQqNs9.md | 4 ++-- .../content/bar-charts@EVk1H-QLtTlpG7lVEenDt.md | 4 ++-- .../big-data-technologies@_aUQZWUhFRvNu0MZ8CPit.md | 6 +++++- .../content/cleanup@nC7tViln4UyQFYP_-fyjB.md | 2 +- .../content/data-cleanup@E6cpb6kvluJM8OGuDcFBT.md | 6 +++++- .../content/data-collection@_sjXCLHHTbZromJYn6fnu.md | 6 +++++- .../data-manipulation-libraries@M1QtGTLyygIjePoCfvjve.md | 8 +++++++- .../data-storage-solutions@iTmtpXe7dR4XKslgpsk2q.md | 4 ++-- .../content/data-transformation@t_BRtEharsrOZxoyX0OzV.md | 2 ++ ...data-visualisation-libraries@l1SnPc4EMqGdaIAhIQfrT.md | 6 ++++-- .../content/data-visualisation@2g19zjEASJw2ve57hxpr0.md | 6 +++++- .../content/databases@tYPeLCxbqvMFlTkCGjdHg.md | 4 ++-- .../content/datedif@yBlJrNo9eO470dLp6OaQZ.md | 2 +- .../deep-learning-optional@SiYUdtYMDImRPmV2_XPkH.md | 6 +++++- .../data-analyst/content/dplyr@v8TfY-b4W5ygOv7r-syHq.md | 2 +- .../data-analyst/content/dplyr@y__UHXe2DD-IB7bvMF1-X.md | 2 +- .../content/ggplot2@E0hIgQEeZlEidr4HtUFrL.md | 4 ++-- .../data-analyst/content/hadoop@wECWIRMlWNoTxz5eKwaSf.md | 4 ++-- .../content/heatmap@G8resQXEVEHCaQfDlt3nj.md | 4 ++-- .../content/image-recognition@bHPJ6yOHtUq5EjJBSrJUE.md | 2 +- .../content/matplotlib@tvDdXwaRPsUSTqJGaLS3P.md | 6 +++--- .../content/matplotlib@uGkXxdMXUMY-3fQFS1jK8.md | 4 ++-- .../data-analyst/content/mode@fY8zVG2tVbmtx5OhY7hj-.md | 2 +- .../model-evaluation-techniques@7ikA373qH88HBx5irCgIH.md | 4 ++-- .../content/neural-networks@gGHsKcS92StK5FolzmVvm.md | 2 +- .../data-analyst/content/pandas@8OXmF2Gn6TYJotBRvDjqA.md | 2 +- .../data-analyst/content/pandas@TucngXKNptbeo3PtdJHX8.md | 2 +- .../content/pie-charts@K9xwm_Vpdup9ujYqlD9F3.md | 6 +++--- .../content/pivot-tables@2DDJUFr0AJTVR2Whj8zub.md | 6 +++--- .../content/power-bi@SJLeose5vZU8w_18C8_t0.md | 2 +- .../predictive-analytics@3WZORRCwme3HsaKew23Z5.md | 4 ++-- .../content/pytorch@LJSqfz6aYJbCe_bK8EWI1.md | 3 ++- .../data-analyst/content/range@tSxtyJhL5wjU0XJcjsJmm.md | 2 +- .../data-analyst/content/rnn@Gocm98_tRg5BGxKcP-7zg.md | 4 ++-- .../content/scatter-plot@A5YQv7D4qRcskdZ64XldH.md | 2 +- .../content/seaborn@-cJb8gEBvdVFf7FlgG3Ud.md | 2 +- .../data-analyst/content/spark@vaiigToDh4522rtWamuSM.md | 2 +- .../content/stacked-charts@329BrtmXjXNLfi1SFfdeo.md | 2 +- .../statistical-analysis@TeewVruErSsD4VLXcaDxp.md | 5 ++++- .../content/supervised-learning@FIYCkGXofKMsXmsqHSMh9.md | 2 +- .../content/tableau@Sz2Y8HLbSmDjSKAJztDql.md | 2 +- .../content/tensorflow@FJ4Sx477FWxyDsQr0R8rl.md | 3 ++- .../types-of-data-analytics@Lsapbmg-eMIYJAHpV97nO.md | 9 +++------ .../unsupervised-learning@FntL9E2yVAYwIrlANDNKE.md | 4 ++-- .../content/variance@ict4JkoVM-AzPbp9bDztg.md | 4 ++-- .../content/visualisation@jowh4CFLQiFzKaaElyCuQ.md | 2 +- .../visualizing-distributions@mCUW07rx74_dUNi7OGVlj.md | 2 +- .../content/vlookup--hlookup@9sIP-jpNjtA1JPCBjTf-H.md | 2 +- .../content/web-scraping@qQ64ZhSlbbWu9pP8KTE67.md | 4 ++-- .../what-is-data-analytics@yCnn-NfSxIybUQ2iTuUGq.md | 6 +++++- 52 files changed, 114 insertions(+), 76 deletions(-) diff --git a/src/data/roadmaps/data-analyst/content/analaysis--reporting-with-excel@sgXIjVTbwdwdYoaxN3XBM.md b/src/data/roadmaps/data-analyst/content/analaysis--reporting-with-excel@sgXIjVTbwdwdYoaxN3XBM.md index d720f00ac..06b5a5e02 100644 --- a/src/data/roadmaps/data-analyst/content/analaysis--reporting-with-excel@sgXIjVTbwdwdYoaxN3XBM.md +++ b/src/data/roadmaps/data-analyst/content/analaysis--reporting-with-excel@sgXIjVTbwdwdYoaxN3XBM.md @@ -2,5 +2,7 @@ Excel is a powerful tool utilized by data analysts worldwide to store, manipulate, and analyze data. It offers a vast array of features such as pivot tables, graphs and a powerful suite of formulas and functions to help sift through large sets of data. A data analyst uses Excel to perform a wide range of tasks, from simple data entry and cleaning, to more complex statistical analysis and predictive modeling. Proficiency in Excel is often a key requirement for a data analyst, as its versatility and ubiquity make it an indispensable tool in the field of data analysis. +Learn more from the following resources: + - [@article@W3Schools - Excel](https://www.w3schools.com/excel/index.php) - [@course@Microsoft Excel Course](https://support.microsoft.com/en-us/office/excel-video-training-9bc05390-e94c-46af-a5b3-d7c22f6990bb) diff --git a/src/data/roadmaps/data-analyst/content/apis@4DFcXSSHxg5wv0uXLIRij.md b/src/data/roadmaps/data-analyst/content/apis@4DFcXSSHxg5wv0uXLIRij.md index 77b7cd064..c838cdc55 100644 --- a/src/data/roadmaps/data-analyst/content/apis@4DFcXSSHxg5wv0uXLIRij.md +++ b/src/data/roadmaps/data-analyst/content/apis@4DFcXSSHxg5wv0uXLIRij.md @@ -5,4 +5,4 @@ Application Programming Interfaces, better known as APIs, play a fundamental rol Learn more from the following resources: - [@article@What is an API?](https://aws.amazon.com/what-is/api/) -- [@article@A beginners guide to APIs](https://www.postman.com/what-is-an-api/) \ No newline at end of file +- [@article@A Beginner's Guide to APIs](https://www.postman.com/what-is-an-api/) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/average@yn1sstYMO9du3rpfQqNs9.md b/src/data/roadmaps/data-analyst/content/average@yn1sstYMO9du3rpfQqNs9.md index 54b3587d1..84b09a2fe 100644 --- a/src/data/roadmaps/data-analyst/content/average@yn1sstYMO9du3rpfQqNs9.md +++ b/src/data/roadmaps/data-analyst/content/average@yn1sstYMO9du3rpfQqNs9.md @@ -1,8 +1,8 @@ -# Average +# Average When focusing on data analysis, understanding key statistical concepts is crucial. Amongst these, central tendency is a foundational element. Central Tendency refers to the measure that determines the center of a distribution. The average is a commonly used statistical tool by which data analysts discern trends and patterns. As one of the most recognized forms of central tendency, figuring out the "average" involves summing all values in a data set and dividing by the number of values. This provides analysts with a 'typical' value, around which the remaining data tends to cluster, facilitating better decision-making based on existing data. Learn more from the following resources: -- [@article@How to calculate the average](https://support.microsoft.com/en-gb/office/calculate-the-average-of-a-group-of-numbers-e158ef61-421c-4839-8290-34d7b1e68283#:~:text=Average%20This%20is%20the%20arithmetic,by%206%2C%20which%20is%205.) +- [@article@How to Calculate the Average](https://support.microsoft.com/en-gb/office/calculate-the-average-of-a-group-of-numbers-e158ef61-421c-4839-8290-34d7b1e68283#:~:text=Average%20This%20is%20the%20arithmetic,by%206%2C%20which%20is%205.) - [@article@Average Formula](https://www.cuemath.com/average-formula/) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/bar-charts@EVk1H-QLtTlpG7lVEenDt.md b/src/data/roadmaps/data-analyst/content/bar-charts@EVk1H-QLtTlpG7lVEenDt.md index 1c1c81af7..0590008da 100644 --- a/src/data/roadmaps/data-analyst/content/bar-charts@EVk1H-QLtTlpG7lVEenDt.md +++ b/src/data/roadmaps/data-analyst/content/bar-charts@EVk1H-QLtTlpG7lVEenDt.md @@ -4,5 +4,5 @@ As a vital tool in the data analyst's arsenal, bar charts are essential for anal Learn more from the following resources: -- [@article@A complete guide to bar charts](https://www.atlassian.com/data/charts/bar-chart-complete-guide) -- [@video@What is a bar chart?](https://www.youtube.com/watch?v=WTVdncVCvKo) \ No newline at end of file +- [@article@A Complete Guide to Bar Charts](https://www.atlassian.com/data/charts/bar-chart-complete-guide) +- [@video@What is a Bar Chart?](https://www.youtube.com/watch?v=WTVdncVCvKo) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/big-data-technologies@_aUQZWUhFRvNu0MZ8CPit.md b/src/data/roadmaps/data-analyst/content/big-data-technologies@_aUQZWUhFRvNu0MZ8CPit.md index 7deab6dff..31ce91065 100644 --- a/src/data/roadmaps/data-analyst/content/big-data-technologies@_aUQZWUhFRvNu0MZ8CPit.md +++ b/src/data/roadmaps/data-analyst/content/big-data-technologies@_aUQZWUhFRvNu0MZ8CPit.md @@ -1,3 +1,7 @@ # Big Data and Data Analyst -In the modern digitized world, Big Data refers to extremely large datasets that are challenging to manage and analyze using traditional data processing applications. These datasets often come from numerous different sources and are not only voluminous but also diverse in nature, including structured and unstructured data. The role of a data analyst in the context of big data is crucial. Data analysts are responsible for inspecting, cleaning, transforming, and modeling big data to discover useful information, conclude and support decision-making. They leverage their analytical skills and various big data tools and technologies to extract insights that can benefit the organization and drive strategic business initiatives. \ No newline at end of file +In the modern digitized world, Big Data refers to extremely large datasets that are challenging to manage and analyze using traditional data processing applications. These datasets often come from numerous different sources and are not only voluminous but also diverse in nature, including structured and unstructured data. The role of a data analyst in the context of big data is crucial. Data analysts are responsible for inspecting, cleaning, transforming, and modeling big data to discover useful information, conclude and support decision-making. They leverage their analytical skills and various big data tools and technologies to extract insights that can benefit the organization and drive strategic business initiatives. + +Learn more from the following resources: + +- [@article@Big Data Analytics](https://www.ibm.com/think/topics/big-data-analytics) diff --git a/src/data/roadmaps/data-analyst/content/cleanup@nC7tViln4UyQFYP_-fyjB.md b/src/data/roadmaps/data-analyst/content/cleanup@nC7tViln4UyQFYP_-fyjB.md index 898a2432e..ce921a9bb 100644 --- a/src/data/roadmaps/data-analyst/content/cleanup@nC7tViln4UyQFYP_-fyjB.md +++ b/src/data/roadmaps/data-analyst/content/cleanup@nC7tViln4UyQFYP_-fyjB.md @@ -4,5 +4,5 @@ The Cleanup of Data is a critical component of a Data Analyst's role. It involve Learn more from the following resources: -- [@article@Top 10 ways to clean your data](https://support.microsoft.com/en-gb/office/top-ten-ways-to-clean-your-data-2844b620-677c-47a7-ac3e-c2e157d1db19) +- [@article@Top 10 Ways to Clean Your Data](https://support.microsoft.com/en-gb/office/top-ten-ways-to-clean-your-data-2844b620-677c-47a7-ac3e-c2e157d1db19) - [@video@Master Data Cleaning Essentials on Excel in Just 10 Minutes](https://www.youtube.com/watch?v=jxq4-KSB_OA) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/data-cleanup@E6cpb6kvluJM8OGuDcFBT.md b/src/data/roadmaps/data-analyst/content/data-cleanup@E6cpb6kvluJM8OGuDcFBT.md index 05a485e75..ef04e3932 100644 --- a/src/data/roadmaps/data-analyst/content/data-cleanup@E6cpb6kvluJM8OGuDcFBT.md +++ b/src/data/roadmaps/data-analyst/content/data-cleanup@E6cpb6kvluJM8OGuDcFBT.md @@ -1,3 +1,7 @@ # Data Cleaning -Data cleaning, which is often referred as data cleansing or data scrubbing, is one of the most important and initial steps in the data analysis process. As a data analyst, the bulk of your work often revolves around understanding, cleaning, and standardizing raw data before analysis. Data cleaning involves identifying, correcting or removing any errors or inconsistencies in datasets in order to improve their quality. The process is crucial because it directly determines the accuracy of the insights you generate - garbage in, garbage out. Even the most sophisticated models and visualizations would not be of much use if they're based on dirty data. Therefore, mastering data cleaning techniques is essential for any data analyst. \ No newline at end of file +Data cleaning, which is often referred as data cleansing or data scrubbing, is one of the most important and initial steps in the data analysis process. As a data analyst, the bulk of your work often revolves around understanding, cleaning, and standardizing raw data before analysis. Data cleaning involves identifying, correcting or removing any errors or inconsistencies in datasets in order to improve their quality. The process is crucial because it directly determines the accuracy of the insights you generate - garbage in, garbage out. Even the most sophisticated models and visualizations would not be of much use if they're based on dirty data. Therefore, mastering data cleaning techniques is essential for any data analyst. + +Learn more from the following resources: + +- [@article@Data Cleaning](https://www.tableau.com/learn/articles/what-is-data-cleaning#:~:text=tools%20and%20software-,What%20is%20data%20cleaning%3F,to%20be%20duplicated%20or%20mislabeled.) diff --git a/src/data/roadmaps/data-analyst/content/data-collection@_sjXCLHHTbZromJYn6fnu.md b/src/data/roadmaps/data-analyst/content/data-collection@_sjXCLHHTbZromJYn6fnu.md index 84cdc070e..e089711b4 100644 --- a/src/data/roadmaps/data-analyst/content/data-collection@_sjXCLHHTbZromJYn6fnu.md +++ b/src/data/roadmaps/data-analyst/content/data-collection@_sjXCLHHTbZromJYn6fnu.md @@ -1,3 +1,7 @@ # Data Collection -In the context of the Data Analyst role, data collection is a foundational process that entails gathering relevant data from various sources. This data can be quantitative or qualitative and may be sourced from databases, online platforms, customer feedback, among others. The gathered information is then cleaned, processed, and interpreted to extract meaningful insights. A data analyst performs this whole process carefully, as the quality of data is paramount to ensuring accurate analysis, which in turn informs business decisions and strategies. This highlights the importance of an excellent understanding, proper tools, and precise techniques when it comes to data collection in data analysis. \ No newline at end of file +Data collection is a foundational process that entails gathering relevant data from various sources. This data can be quantitative or qualitative and may be sourced from databases, online platforms, customer feedback, among others. The gathered information is then cleaned, processed, and interpreted to extract meaningful insights. A data analyst performs this whole process carefully, as the quality of data is paramount to ensuring accurate analysis, which in turn informs business decisions and strategies. This highlights the importance of an excellent understanding, proper tools, and precise techniques when it comes to data collection in data analysis. + +Learn more from the following resources: + +- [@article@Data Collection](https://en.wikipedia.org/wiki/Data_collection) diff --git a/src/data/roadmaps/data-analyst/content/data-manipulation-libraries@M1QtGTLyygIjePoCfvjve.md b/src/data/roadmaps/data-analyst/content/data-manipulation-libraries@M1QtGTLyygIjePoCfvjve.md index 67bcc376d..6fe90c059 100644 --- a/src/data/roadmaps/data-analyst/content/data-manipulation-libraries@M1QtGTLyygIjePoCfvjve.md +++ b/src/data/roadmaps/data-analyst/content/data-manipulation-libraries@M1QtGTLyygIjePoCfvjve.md @@ -1,3 +1,9 @@ # Data Manipulation Libraries -Data manipulation libraries are essential tools in data science and analytics, enabling efficient handling, transformation, and analysis of large datasets. Python, a popular language for data science, offers several powerful libraries for this purpose. Pandas is a highly versatile library that provides data structures like DataFrames, which allow for easy manipulation and analysis of tabular data. NumPy, another fundamental library, offers support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays. Together, Pandas and NumPy form the backbone of data manipulation in Python, facilitating tasks such as data cleaning, merging, reshaping, and statistical analysis, thus streamlining the data preparation process for machine learning and other data-driven applications. \ No newline at end of file +Data manipulation libraries are essential tools in data science and analytics, enabling efficient handling, transformation, and analysis of large datasets. Python, a popular language for data science, offers several powerful libraries for this purpose. Pandas is a highly versatile library that provides data structures like DataFrames, which allow for easy manipulation and analysis of tabular data. NumPy, another fundamental library, offers support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays. Together, Pandas and NumPy form the backbone of data manipulation in Python, facilitating tasks such as data cleaning, merging, reshaping, and statistical analysis, thus streamlining the data preparation process for machine learning and other data-driven applications. + +Learn more from the following resources: + +- [@article@Pandas](https://pandas.pydata.org/) +- [@article@NumPy](https://numpy.org/) +- [@article@Top Python Libraries for Data Science](https://www.simplilearn.com/top-python-libraries-for-data-science-article) diff --git a/src/data/roadmaps/data-analyst/content/data-storage-solutions@iTmtpXe7dR4XKslgpsk2q.md b/src/data/roadmaps/data-analyst/content/data-storage-solutions@iTmtpXe7dR4XKslgpsk2q.md index 7457deca6..01a777d36 100644 --- a/src/data/roadmaps/data-analyst/content/data-storage-solutions@iTmtpXe7dR4XKslgpsk2q.md +++ b/src/data/roadmaps/data-analyst/content/data-storage-solutions@iTmtpXe7dR4XKslgpsk2q.md @@ -4,5 +4,5 @@ As a business enterprise expands, so does its data. For data analysts, the surge Learn more from the following resources: -- [@official@SQL Roadmap](https://roadmap.sh/sql) -- [@official@PostgreSQL Roadmap](https://roadmap.sh/postgresql-dba) \ No newline at end of file +- [@roadmap@Visit Dedicated SQL Roadmap](https://roadmap.sh/sql) +- [@roadmap@Visit Dedicated PostgreSQL Roadmap](https://roadmap.sh/postgresql-dba) diff --git a/src/data/roadmaps/data-analyst/content/data-transformation@t_BRtEharsrOZxoyX0OzV.md b/src/data/roadmaps/data-analyst/content/data-transformation@t_BRtEharsrOZxoyX0OzV.md index 6f5ced344..fed65dd76 100644 --- a/src/data/roadmaps/data-analyst/content/data-transformation@t_BRtEharsrOZxoyX0OzV.md +++ b/src/data/roadmaps/data-analyst/content/data-transformation@t_BRtEharsrOZxoyX0OzV.md @@ -2,5 +2,7 @@ Data Transformation, also known as Data Wrangling, is an essential part of a Data Analyst's role. This process involves the conversion of data from a raw format into another format to make it more appropriate and valuable for a variety of downstream purposes such as analytics. Data Analysts transform data to make the data more suitable for analysis, ensure accuracy, and to improve data quality. The right transformation techniques can give the data a structure, multiply its value, and enhance the accuracy of the analytics performed by serving meaningful results. +Learn more from the following resources: + - [@article@What is data transformation?](https://www.qlik.com/us/data-management/data-transformation) - [@feed@Explore top posts about Data Analysis](https://app.daily.dev/tags/data-analysis?ref=roadmapsh) diff --git a/src/data/roadmaps/data-analyst/content/data-visualisation-libraries@l1SnPc4EMqGdaIAhIQfrT.md b/src/data/roadmaps/data-analyst/content/data-visualisation-libraries@l1SnPc4EMqGdaIAhIQfrT.md index 9c28a83ea..cad2c533e 100644 --- a/src/data/roadmaps/data-analyst/content/data-visualisation-libraries@l1SnPc4EMqGdaIAhIQfrT.md +++ b/src/data/roadmaps/data-analyst/content/data-visualisation-libraries@l1SnPc4EMqGdaIAhIQfrT.md @@ -1,3 +1,5 @@ -# Data Visualisation Libraries +# Data Visualization Libraries -Data visualization libraries are crucial in data science for transforming complex datasets into clear and interpretable visual representations, facilitating better understanding and communication of data insights. In Python, several libraries are widely used for this purpose. Matplotlib is a foundational library that offers comprehensive tools for creating static, animated, and interactive plots. Seaborn, built on top of Matplotlib, provides a high-level interface for drawing attractive and informative statistical graphics with minimal code. Plotly is another powerful library that allows for the creation of interactive and dynamic visualizations, which can be easily embedded in web applications. Additionally, libraries like Bokeh and Altair offer capabilities for creating interactive plots and dashboards, enhancing exploratory data analysis and the presentation of data findings. Together, these libraries enable data scientists to effectively visualize trends, patterns, and outliers in their data, making the analysis more accessible and actionable. \ No newline at end of file +Data visualization libraries are crucial in data science for transforming complex datasets into clear and interpretable visual representations, facilitating better understanding and communication of data insights. In Python, several libraries are widely used for this purpose. Matplotlib is a foundational library that offers comprehensive tools for creating static, animated, and interactive plots. Seaborn, built on top of Matplotlib, provides a high-level interface for drawing attractive and informative statistical graphics with minimal code. Plotly is another powerful library that allows for the creation of interactive and dynamic visualizations, which can be easily embedded in web applications. Additionally, libraries like Bokeh and Altair offer capabilities for creating interactive plots and dashboards, enhancing exploratory data analysis and the presentation of data findings. Together, these libraries enable data scientists to effectively visualize trends, patterns, and outliers in their data, making the analysis more accessible and actionable. + +Learn more from the following resources: diff --git a/src/data/roadmaps/data-analyst/content/data-visualisation@2g19zjEASJw2ve57hxpr0.md b/src/data/roadmaps/data-analyst/content/data-visualisation@2g19zjEASJw2ve57hxpr0.md index 1a1b59ed5..0cd3f4518 100644 --- a/src/data/roadmaps/data-analyst/content/data-visualisation@2g19zjEASJw2ve57hxpr0.md +++ b/src/data/roadmaps/data-analyst/content/data-visualisation@2g19zjEASJw2ve57hxpr0.md @@ -1,3 +1,7 @@ # Data Visualization -Data Visualization is a fundamental fragment of the responsibilities of a data analyst. It involves the presentation of data in a graphical or pictorial format which allows decision-makers to see analytics visually. This practice can help them comprehend difficult concepts or establish new patterns. With interactive visualization, data analysts can take the data analysis process to a whole new level — drill down into charts and graphs for more detail, and interactively changing what data is presented or how it’s processed. Thereby it forms a crucial link in the chain of converting raw data to actionable insights which is one of the primary roles of a Data Analyst. \ No newline at end of file +Data Visualization is a fundamental fragment of the responsibilities of a data analyst. It involves the presentation of data in a graphical or pictorial format which allows decision-makers to see analytics visually. This practice can help them comprehend difficult concepts or establish new patterns. With interactive visualization, data analysts can take the data analysis process to a whole new level — drill down into charts and graphs for more detail, and interactively changing what data is presented or how it’s processed. Thereby it forms a crucial link in the chain of converting raw data to actionable insights which is one of the primary roles of a Data Analyst. + +Learn more from the following resources: + +- [@article@What is Data Visualization?](https://www.ibm.com/think/topics/data-visualization) diff --git a/src/data/roadmaps/data-analyst/content/databases@tYPeLCxbqvMFlTkCGjdHg.md b/src/data/roadmaps/data-analyst/content/databases@tYPeLCxbqvMFlTkCGjdHg.md index 68787c059..d532dccff 100644 --- a/src/data/roadmaps/data-analyst/content/databases@tYPeLCxbqvMFlTkCGjdHg.md +++ b/src/data/roadmaps/data-analyst/content/databases@tYPeLCxbqvMFlTkCGjdHg.md @@ -4,5 +4,5 @@ Behind every strong data analyst, there's not just a rich assortment of data, bu Learn more from the following resources: -- [@official@PostgreSQL Roadmap](https://roadmap.sh/postgresql-dba) -- [@official@MongoDB Roadmap](https://roadmap.sh/mongodb) \ No newline at end of file +- [@roadmap@Visit Dedicated SQL Roadmap](https://roadmap.sh/sql) +- [@roadmap@Visit Dedicated PostgreSQL Roadmap](https://roadmap.sh/postgresql-dba) diff --git a/src/data/roadmaps/data-analyst/content/datedif@yBlJrNo9eO470dLp6OaQZ.md b/src/data/roadmaps/data-analyst/content/datedif@yBlJrNo9eO470dLp6OaQZ.md index 8b613e6bf..49dffdf7f 100644 --- a/src/data/roadmaps/data-analyst/content/datedif@yBlJrNo9eO470dLp6OaQZ.md +++ b/src/data/roadmaps/data-analyst/content/datedif@yBlJrNo9eO470dLp6OaQZ.md @@ -2,7 +2,7 @@ The `DATEDIF` function is an incredibly valuable tool for a Data Analyst in Excel or Google Sheets, by providing the ability to calculate the difference between two dates. This function takes in three parameters: start date, end date and the type of difference required (measured in years, months, days, etc.). In Data Analysis, particularly when dealing with time-series data or when you need to uncover trends over specific periods, the `DATEDIF` function is a necessary asset. Recognizing its functionality will enable a data analyst to manipulate or shape data progressively and efficiently. -* `DATEDIF` is technically still supported, but wont show as an option. For additional information, see Excel "Help" page. +`DATEDIF` is technically still supported, but wont show as an option. For additional information, see Excel "Help" page. Learn more from the following resources: diff --git a/src/data/roadmaps/data-analyst/content/deep-learning-optional@SiYUdtYMDImRPmV2_XPkH.md b/src/data/roadmaps/data-analyst/content/deep-learning-optional@SiYUdtYMDImRPmV2_XPkH.md index a9af1484c..ee63c6640 100644 --- a/src/data/roadmaps/data-analyst/content/deep-learning-optional@SiYUdtYMDImRPmV2_XPkH.md +++ b/src/data/roadmaps/data-analyst/content/deep-learning-optional@SiYUdtYMDImRPmV2_XPkH.md @@ -1,3 +1,7 @@ # Deep Learning and Data Analysis -Deep learning, a subset of machine learning technique, is increasingly becoming a critical tool for data analysts. Deep learning algorithms utilize multiple layers of neural networks to understand and interpret intricate structures in large data, a skill that is integral to the daily functions of a data analyst. With the ability to learn from unstructured or unlabeled data, deep learning opens a whole new range of possibilities for data analysts in terms of data processing, prediction, and categorization. It has applications in a variety of industries from healthcare to finance to e-commerce and beyond. A deeper understanding of deep learning methodologies can augment a data analyst's capability to evaluate and interpret complex datasets and provide valuable insights for decision making. \ No newline at end of file +Deep learning, a subset of machine learning technique, is increasingly becoming a critical tool for data analysts. Deep learning algorithms utilize multiple layers of neural networks to understand and interpret intricate structures in large data, a skill that is integral to the daily functions of a data analyst. With the ability to learn from unstructured or unlabeled data, deep learning opens a whole new range of possibilities for data analysts in terms of data processing, prediction, and categorization. It has applications in a variety of industries from healthcare to finance to e-commerce and beyond. A deeper understanding of deep learning methodologies can augment a data analyst's capability to evaluate and interpret complex datasets and provide valuable insights for decision making. + +Learn more from the following resources: + +- [@article@Deep Learning for Data Analysis](https://www.ibm.com/think/topics/deep-learning) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/dplyr@v8TfY-b4W5ygOv7r-syHq.md b/src/data/roadmaps/data-analyst/content/dplyr@v8TfY-b4W5ygOv7r-syHq.md index d1be37cfc..a3e5688cf 100644 --- a/src/data/roadmaps/data-analyst/content/dplyr@v8TfY-b4W5ygOv7r-syHq.md +++ b/src/data/roadmaps/data-analyst/content/dplyr@v8TfY-b4W5ygOv7r-syHq.md @@ -4,5 +4,5 @@ Data cleaning plays a crucial role in the data analysis pipeline, where it recti Learn more from the following resources: -- [@official@dplyr website](https://dplyr.tidyverse.org/) +- [@official@dplyr](https://dplyr.tidyverse.org/) - [@video@Dplyr Essentials](https://www.youtube.com/watch?v=Gvhkp-Yw65U) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/dplyr@y__UHXe2DD-IB7bvMF1-X.md b/src/data/roadmaps/data-analyst/content/dplyr@y__UHXe2DD-IB7bvMF1-X.md index 57ede3dec..3e575b264 100644 --- a/src/data/roadmaps/data-analyst/content/dplyr@y__UHXe2DD-IB7bvMF1-X.md +++ b/src/data/roadmaps/data-analyst/content/dplyr@y__UHXe2DD-IB7bvMF1-X.md @@ -4,5 +4,5 @@ Dplyr is a powerful and popular toolkit for data manipulation in R. As a data an Learn more from the following resources: -- [@official@dplyr website](https://dplyr.tidyverse.org/) +- [@official@dplyr](https://dplyr.tidyverse.org/) - [@video@Dplyr Essentials](https://www.youtube.com/watch?v=Gvhkp-Yw65U) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/ggplot2@E0hIgQEeZlEidr4HtUFrL.md b/src/data/roadmaps/data-analyst/content/ggplot2@E0hIgQEeZlEidr4HtUFrL.md index e5c96fa9b..20cd3eb37 100644 --- a/src/data/roadmaps/data-analyst/content/ggplot2@E0hIgQEeZlEidr4HtUFrL.md +++ b/src/data/roadmaps/data-analyst/content/ggplot2@E0hIgQEeZlEidr4HtUFrL.md @@ -1,8 +1,8 @@ -# ggplot2 +# ggplot2 When it comes to data visualization in R programming, ggplot2 stands tall as one of the primary tools for data analysts. This data visualization library, which forms part of the tidyverse suite of packages, facilitates the creation of complex and sophisticated visual narratives. With its grammar of graphics philosophy, ggplot2 enables analysts to build graphs and charts layer by layer, thereby offering detailed control over graphical features and design. Its versatility in creating tailored and aesthetically pleasing graphics is a vital asset for any data analyst tackling exploratory data analysis, reporting, or dashboard building. Learn more from the following resources: -- [@article@ggplot2 website](https://ggplot2.tidyverse.org/) +- [@official@ggplot2](https://ggplot2.tidyverse.org/) - [@video@Make beautiful graphs in R](https://www.youtube.com/watch?v=qnw1xDnt_Ec) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/hadoop@wECWIRMlWNoTxz5eKwaSf.md b/src/data/roadmaps/data-analyst/content/hadoop@wECWIRMlWNoTxz5eKwaSf.md index cecdeccab..4f007ce6f 100644 --- a/src/data/roadmaps/data-analyst/content/hadoop@wECWIRMlWNoTxz5eKwaSf.md +++ b/src/data/roadmaps/data-analyst/content/hadoop@wECWIRMlWNoTxz5eKwaSf.md @@ -1,8 +1,8 @@ -# Hadoop +# Hadoop Hadoop is a critical element in the realm of data processing frameworks, offering an effective solution for storing, managing, and analyzing massive amounts of data. Unraveling meaningful insights from a large deluge of data is a challenging pursuit faced by many data analysts. Regular data processing tools fail to handle large-scale data, paving the way for advanced frameworks like Hadoop. This open-source platform by Apache Software Foundation excels at storing and processing vast data across clusters of computers. Notably, Hadoop comprises two key modules - the Hadoop Distributed File System (HDFS) for storage and MapReduce for processing. Hadoop’s ability to handle both structured and unstructured data further broadens its capacity. For any data analyst, a thorough understanding of Hadoop can unlock powerful ways to manage data effectively and construct meaningful analytics. Learn more from the following resources: -- [@official@Apache Hadoop Website](https://hadoop.apache.org/) +- [@official@Apache Hadoop](https://hadoop.apache.org/) - [@article@What Is Hadoop?](https://www.databricks.com/glossary/hadoop) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/heatmap@G8resQXEVEHCaQfDlt3nj.md b/src/data/roadmaps/data-analyst/content/heatmap@G8resQXEVEHCaQfDlt3nj.md index f54dbe442..986371acc 100644 --- a/src/data/roadmaps/data-analyst/content/heatmap@G8resQXEVEHCaQfDlt3nj.md +++ b/src/data/roadmaps/data-analyst/content/heatmap@G8resQXEVEHCaQfDlt3nj.md @@ -4,5 +4,5 @@ Heatmaps are a crucial component of data visualization that Data Analysts regula Learn more from the following resources: -- [@article@A complete guide to heatmaps](https://www.hotjar.com/heatmaps/) -- [@article@What is a heatmap?](https://www.atlassian.com/data/charts/heatmap-complete-guide) \ No newline at end of file +- [@article@A Complete Guide to Heatmaps](https://www.hotjar.com/heatmaps/) +- [@article@What is a Heatmap?](https://www.atlassian.com/data/charts/heatmap-complete-guide) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/image-recognition@bHPJ6yOHtUq5EjJBSrJUE.md b/src/data/roadmaps/data-analyst/content/image-recognition@bHPJ6yOHtUq5EjJBSrJUE.md index 3c7896d62..11bf2b190 100644 --- a/src/data/roadmaps/data-analyst/content/image-recognition@bHPJ6yOHtUq5EjJBSrJUE.md +++ b/src/data/roadmaps/data-analyst/content/image-recognition@bHPJ6yOHtUq5EjJBSrJUE.md @@ -4,5 +4,5 @@ Image Recognition has become a significant domain because of its diverse applica Learn more from the following resources: -- [@article@What is image recognition?](https://www.techtarget.com/searchenterpriseai/definition/image-recognition) +- [@article@What is Image Recognition?](https://www.techtarget.com/searchenterpriseai/definition/image-recognition) - [@article@Image Recognition: Definition, Algorithms & Uses](https://www.v7labs.com/blog/image-recognition-guide) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/matplotlib@tvDdXwaRPsUSTqJGaLS3P.md b/src/data/roadmaps/data-analyst/content/matplotlib@tvDdXwaRPsUSTqJGaLS3P.md index 8fb1af9ee..b7932c55f 100644 --- a/src/data/roadmaps/data-analyst/content/matplotlib@tvDdXwaRPsUSTqJGaLS3P.md +++ b/src/data/roadmaps/data-analyst/content/matplotlib@tvDdXwaRPsUSTqJGaLS3P.md @@ -1,8 +1,8 @@ -# Matplotlib +# Matplotlib For a Data Analyst, understanding data and being able to represent it in a visually insightful form is a crucial part of effective decision-making in any organization. Matplotlib, a plotting library for the Python programming language, is an extremely useful tool for this purpose. It presents a versatile framework for generating line plots, scatter plots, histogram, bar charts and much more in a very straightforward manner. This library also allows for comprehensive customizations, offering a high level of control over the look and feel of the graphics it produces, which ultimately enhances the quality of data interpretation and communication. Learn more from the following resources: -- [@video@Learn Matplotlib in 6 minutes](https://www.youtube.com/watch?v=nzKy9GY12yo) -- [@article@Matplotlib Website](https://matplotlib.org/) \ No newline at end of file +- [@official@Matplotlib](https://matplotlib.org/) +- [@video@Learn Matplotlib in 6 minutes](https://www.youtube.com/watch?v=nzKy9GY12yo) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/matplotlib@uGkXxdMXUMY-3fQFS1jK8.md b/src/data/roadmaps/data-analyst/content/matplotlib@uGkXxdMXUMY-3fQFS1jK8.md index 64c64e65a..d4d612457 100644 --- a/src/data/roadmaps/data-analyst/content/matplotlib@uGkXxdMXUMY-3fQFS1jK8.md +++ b/src/data/roadmaps/data-analyst/content/matplotlib@uGkXxdMXUMY-3fQFS1jK8.md @@ -4,5 +4,5 @@ Matplotlib is a paramount data visualization library used extensively by data an Learn more from the following resources: -- [@video@Learn Matplotlib in 6 minutes](https://www.youtube.com/watch?v=nzKy9GY12yo) -- [@article@Matplotlib Website](https://matplotlib.org/) \ No newline at end of file +- [@official@Matplotlib](https://matplotlib.org/) +- [@video@Learn Matplotlib in 6 minutes](https://www.youtube.com/watch?v=nzKy9GY12yo) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/mode@fY8zVG2tVbmtx5OhY7hj-.md b/src/data/roadmaps/data-analyst/content/mode@fY8zVG2tVbmtx5OhY7hj-.md index 8cf1b0abc..c31de880b 100644 --- a/src/data/roadmaps/data-analyst/content/mode@fY8zVG2tVbmtx5OhY7hj-.md +++ b/src/data/roadmaps/data-analyst/content/mode@fY8zVG2tVbmtx5OhY7hj-.md @@ -2,7 +2,7 @@ The concept of central tendency is fundamental in statistics and has numerous applications in data analysis. From a data analyst's perspective, the central tendencies like mean, median, and mode can be highly informative about the nature of data. Among these, the "Mode" is often underappreciated, yet it plays an essential role in interpreting datasets. -The mode, in essence, represents the most frequently occurring value in a dataset. While it may appear simplistic, the mode's ability to identify the most common value can be instrumental in a wide range of scenarios, like market research, customer behavior analysis, or trend identification. For instance, a data analyst can use the mode to determine the most popular product in a sales dataset or identify the most commonly reported bug in a software bug log. +The mode, in essence, represents the most frequently occurring value in a dataset. While it may appear simplistic, the mode's ability to identify the most common value can be instrumental in a wide range of scenarios, like market research, customer behavior analysis, or trend identification. For instance, a data analyst can use the mode to determine the most popular product in a sales dataset or identify the most commonly reported bug in a software bug log. Beyond these, utilizing the mode along with the other measures of central tendency (mean and median) can provide a more rounded view of your data. This approach personifies the diversity that's often required in data analytic strategies to account for different data distributions and outliers. The mode, therefore, forms an integral part of the data analyst's toolkit for statistical data interpretation. diff --git a/src/data/roadmaps/data-analyst/content/model-evaluation-techniques@7ikA373qH88HBx5irCgIH.md b/src/data/roadmaps/data-analyst/content/model-evaluation-techniques@7ikA373qH88HBx5irCgIH.md index 81f7145c0..455de0591 100644 --- a/src/data/roadmaps/data-analyst/content/model-evaluation-techniques@7ikA373qH88HBx5irCgIH.md +++ b/src/data/roadmaps/data-analyst/content/model-evaluation-techniques@7ikA373qH88HBx5irCgIH.md @@ -4,5 +4,5 @@ As a data analyst, it's crucial to understand various model evaluation technique Learn more from the following resources: -- [@article@What is model evaluation](https://domino.ai/data-science-dictionary/model-evaluation) -- [@article@Model evaluation metrics](https://www.markovml.com/blog/model-evaluation-metrics) \ No newline at end of file +- [@article@What is Model Evaluation](https://domino.ai/data-science-dictionary/model-evaluation) +- [@article@Model Evaluation Metrics](https://www.markovml.com/blog/model-evaluation-metrics) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/neural-networks@gGHsKcS92StK5FolzmVvm.md b/src/data/roadmaps/data-analyst/content/neural-networks@gGHsKcS92StK5FolzmVvm.md index 3eb852182..6d8e9d4d5 100644 --- a/src/data/roadmaps/data-analyst/content/neural-networks@gGHsKcS92StK5FolzmVvm.md +++ b/src/data/roadmaps/data-analyst/content/neural-networks@gGHsKcS92StK5FolzmVvm.md @@ -4,5 +4,5 @@ Neural Networks play a pivotal role in the landscape of deep learning, offering Learn more from the following resources: -- [@article@What is a neural network?](https://aws.amazon.com/what-is/neural-network/) +- [@article@What is a Neural Network?](https://aws.amazon.com/what-is/neural-network/) - [@article@Explained: Neural networks](https://news.mit.edu/2017/explained-neural-networks-deep-learning-0414) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/pandas@8OXmF2Gn6TYJotBRvDjqA.md b/src/data/roadmaps/data-analyst/content/pandas@8OXmF2Gn6TYJotBRvDjqA.md index 11434323b..aa0054af8 100644 --- a/src/data/roadmaps/data-analyst/content/pandas@8OXmF2Gn6TYJotBRvDjqA.md +++ b/src/data/roadmaps/data-analyst/content/pandas@8OXmF2Gn6TYJotBRvDjqA.md @@ -4,5 +4,5 @@ Pandas is a widely acknowledged and highly useful data manipulation library in t Learn more from the following resources: -- [@official@Pandas Website](https://pandas.pydata.org/) +- [@official@Pandas](https://pandas.pydata.org/) - [@video@NumPy vs Pandas](https://www.youtube.com/watch?v=KHoEbRH46Zk) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/pandas@TucngXKNptbeo3PtdJHX8.md b/src/data/roadmaps/data-analyst/content/pandas@TucngXKNptbeo3PtdJHX8.md index c55ac6d4e..169d59896 100644 --- a/src/data/roadmaps/data-analyst/content/pandas@TucngXKNptbeo3PtdJHX8.md +++ b/src/data/roadmaps/data-analyst/content/pandas@TucngXKNptbeo3PtdJHX8.md @@ -4,5 +4,5 @@ In the realms of data analysis, data cleaning is a crucial preliminary process, Learn more from the following resources: -- [@official@Pandas Website](https://pandas.pydata.org/) +- [@official@Pandas](https://pandas.pydata.org/) - [@video@NumPy vs Pandas](https://www.youtube.com/watch?v=KHoEbRH46Zk) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/pie-charts@K9xwm_Vpdup9ujYqlD9F3.md b/src/data/roadmaps/data-analyst/content/pie-charts@K9xwm_Vpdup9ujYqlD9F3.md index 0cd9a1b24..f11cb736d 100644 --- a/src/data/roadmaps/data-analyst/content/pie-charts@K9xwm_Vpdup9ujYqlD9F3.md +++ b/src/data/roadmaps/data-analyst/content/pie-charts@K9xwm_Vpdup9ujYqlD9F3.md @@ -1,8 +1,8 @@ -# Pie Chart +# Pie Chart As a data analyst, understanding and efficiently using various forms of data visualization is crucial. Among these, Pie Charts represent a significant tool. Essentially, pie charts are circular statistical graphics divided into slices to illustrate numerical proportions. Each slice of the pie corresponds to a particular category. The pie chart's beauty lies in its simplicity and visual appeal, making it an effective way to convey relative proportions or percentages at a glance. For a data analyst, it's particularly useful when you want to show a simple distribution of categorical data. Like any tool, though, it's important to use pie charts wisely—ideally, when your data set has fewer than seven categories, and the proportions between categories are distinct. Learn more from the following resources: -- [@video@What is a a pie chart](https://www.youtube.com/watch?v=GjJdZaQrItg) -- [@article@A complete guide to pie charts](https://www.atlassian.com/data/charts/pie-chart-complete-guide) \ No newline at end of file +- [@video@What is a Pie Chart](https://www.youtube.com/watch?v=GjJdZaQrItg) +- [@article@A Complete Guide to Pie Charts](https://www.atlassian.com/data/charts/pie-chart-complete-guide) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/pivot-tables@2DDJUFr0AJTVR2Whj8zub.md b/src/data/roadmaps/data-analyst/content/pivot-tables@2DDJUFr0AJTVR2Whj8zub.md index d0a3cb959..96e669754 100644 --- a/src/data/roadmaps/data-analyst/content/pivot-tables@2DDJUFr0AJTVR2Whj8zub.md +++ b/src/data/roadmaps/data-analyst/content/pivot-tables@2DDJUFr0AJTVR2Whj8zub.md @@ -4,6 +4,6 @@ Data Analysts recurrently find the need to summarize, investigate, and analyze t Learn more from the following resources: -- [@articles@Create a pivot table](https://support.microsoft.com/en-gb/office/create-a-pivottable-to-analyze-worksheet-data-a9a84538-bfe9-40a9-a8e9-f99134456576) -- [@article@Pivot tables in excel](https://www.excel-easy.com/data-analysis/pivot-tables.html) -- [@video@How to create a pivot table in excel](https://www.youtube.com/watch?v=PdJzy956wo4) \ No newline at end of file +- [@articles@Create a Pivot Table](https://support.microsoft.com/en-gb/office/create-a-pivottable-to-analyze-worksheet-data-a9a84538-bfe9-40a9-a8e9-f99134456576) +- [@article@Pivot Tables in Excel](https://www.excel-easy.com/data-analysis/pivot-tables.html) +- [@video@How to Create a Pivot Table in Excel](https://www.youtube.com/watch?v=PdJzy956wo4) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/power-bi@SJLeose5vZU8w_18C8_t0.md b/src/data/roadmaps/data-analyst/content/power-bi@SJLeose5vZU8w_18C8_t0.md index d716d307d..0dfdb062e 100644 --- a/src/data/roadmaps/data-analyst/content/power-bi@SJLeose5vZU8w_18C8_t0.md +++ b/src/data/roadmaps/data-analyst/content/power-bi@SJLeose5vZU8w_18C8_t0.md @@ -4,5 +4,5 @@ PowerBI, an interactive data visualization and business analytics tool developed Learn more from the following resources: -- [@official@Power BI Website](https://www.microsoft.com/en-us/power-platform/products/power-bi) +- [@official@Power BI](https://www.microsoft.com/en-us/power-platform/products/power-bi) - [@video@Power BI for beginners](https://www.youtube.com/watch?v=NNSHu0rkew8) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/predictive-analytics@3WZORRCwme3HsaKew23Z5.md b/src/data/roadmaps/data-analyst/content/predictive-analytics@3WZORRCwme3HsaKew23Z5.md index a60c7d208..2b2016787 100644 --- a/src/data/roadmaps/data-analyst/content/predictive-analytics@3WZORRCwme3HsaKew23Z5.md +++ b/src/data/roadmaps/data-analyst/content/predictive-analytics@3WZORRCwme3HsaKew23Z5.md @@ -4,5 +4,5 @@ Predictive analysis is a crucial type of data analytics that any competent data Learn more from the following resources: -- [@video@What is predictive analytics?](https://www.youtube.com/watch?v=cVibCHRSxB0) -- [@article@What is predictive analytics? - Google](https://cloud.google.com/learn/what-is-predictive-analytics) \ No newline at end of file +- [@video@What is Predictive Analytics?](https://www.youtube.com/watch?v=cVibCHRSxB0) +- [@article@What is Predictive Analytics? - Google](https://cloud.google.com/learn/what-is-predictive-analytics) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/pytorch@LJSqfz6aYJbCe_bK8EWI1.md b/src/data/roadmaps/data-analyst/content/pytorch@LJSqfz6aYJbCe_bK8EWI1.md index 36e838043..62c8a7b35 100644 --- a/src/data/roadmaps/data-analyst/content/pytorch@LJSqfz6aYJbCe_bK8EWI1.md +++ b/src/data/roadmaps/data-analyst/content/pytorch@LJSqfz6aYJbCe_bK8EWI1.md @@ -4,5 +4,6 @@ PyTorch, an open-source machine learning library, has gained considerable popula Learn more from the following resources: -- [@official@PyTorch Website](https://pytorch.org/) +- [@official@PyTorch](https://pytorch.org/) +- [@official@PyTorch Documentation](https://pytorch.org/docs/stable/index.html) - [@video@PyTorch in 100 seconds](https://www.youtube.com/watch?v=ORMx45xqWkA) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/range@tSxtyJhL5wjU0XJcjsJmm.md b/src/data/roadmaps/data-analyst/content/range@tSxtyJhL5wjU0XJcjsJmm.md index 5f8c24d01..de8f7dd18 100644 --- a/src/data/roadmaps/data-analyst/content/range@tSxtyJhL5wjU0XJcjsJmm.md +++ b/src/data/roadmaps/data-analyst/content/range@tSxtyJhL5wjU0XJcjsJmm.md @@ -4,4 +4,4 @@ The concept of Range refers to the spread of a dataset, primarily in the realm o Learn more from the following resources: -- [@article@How to find the range of a data set](https://www.scribbr.co.uk/stats/range-statistics/) \ No newline at end of file +- [@article@How to Find the Range of a Data Set](https://www.scribbr.co.uk/stats/range-statistics/) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/rnn@Gocm98_tRg5BGxKcP-7zg.md b/src/data/roadmaps/data-analyst/content/rnn@Gocm98_tRg5BGxKcP-7zg.md index 267a9e499..8d1965fc3 100644 --- a/src/data/roadmaps/data-analyst/content/rnn@Gocm98_tRg5BGxKcP-7zg.md +++ b/src/data/roadmaps/data-analyst/content/rnn@Gocm98_tRg5BGxKcP-7zg.md @@ -6,5 +6,5 @@ A data analyst leveraging RNNs can effectively charter the intrinsic complexity Learn more from the following resources: -- [@article@What is a recurrent neural network (RNN)?](https://www.ibm.com/topics/recurrent-neural-networks) -- [@article@Recurrent Neural Networks cheatsheet](https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-recurrent-neural-networks) \ No newline at end of file +- [@article@What is a Recurrent Neural Network (RNN)?](https://www.ibm.com/topics/recurrent-neural-networks) +- [@article@Recurrent Neural Networks Cheat-sheet](https://stanford.edu/~shervine/teaching/cs-230/cheatsheet-recurrent-neural-networks) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/scatter-plot@A5YQv7D4qRcskdZ64XldH.md b/src/data/roadmaps/data-analyst/content/scatter-plot@A5YQv7D4qRcskdZ64XldH.md index a8bddcefd..5b7f12bbd 100644 --- a/src/data/roadmaps/data-analyst/content/scatter-plot@A5YQv7D4qRcskdZ64XldH.md +++ b/src/data/roadmaps/data-analyst/content/scatter-plot@A5YQv7D4qRcskdZ64XldH.md @@ -4,5 +4,5 @@ A scatter plot, a crucial aspect of data visualization, is a mathematical diagra Learn more from the following resources: -- [@article@Mastering scatter plots](https://www.atlassian.com/data/charts/what-is-a-scatter-plot) +- [@article@Mastering Scatter Plots](https://www.atlassian.com/data/charts/what-is-a-scatter-plot) - [@video@Scatter Graphs: What are they and how to plot them](https://www.youtube.com/watch?v=Vyg9qmBsgAc) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/seaborn@-cJb8gEBvdVFf7FlgG3Ud.md b/src/data/roadmaps/data-analyst/content/seaborn@-cJb8gEBvdVFf7FlgG3Ud.md index 05c9d1ae1..f0d09f5e3 100644 --- a/src/data/roadmaps/data-analyst/content/seaborn@-cJb8gEBvdVFf7FlgG3Ud.md +++ b/src/data/roadmaps/data-analyst/content/seaborn@-cJb8gEBvdVFf7FlgG3Ud.md @@ -4,5 +4,5 @@ Seaborn is a robust, comprehensive Python library focused on the creation of inf Learn more from the following resources: -- [@official@Seaborn Website](https://seaborn.pydata.org/) +- [@official@Seaborn](https://seaborn.pydata.org/) - [@video@Seaborn Tutorial : Seaborn Full Course](https://www.youtube.com/watch?v=6GUZXDef2U0) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/spark@vaiigToDh4522rtWamuSM.md b/src/data/roadmaps/data-analyst/content/spark@vaiigToDh4522rtWamuSM.md index 63cfa6f38..a626ac638 100644 --- a/src/data/roadmaps/data-analyst/content/spark@vaiigToDh4522rtWamuSM.md +++ b/src/data/roadmaps/data-analyst/content/spark@vaiigToDh4522rtWamuSM.md @@ -4,5 +4,5 @@ As a big data processing framework, Apache Spark showcases immense importance in Learn more from the following resources: -- [@official@Apache Spark Website](https://spark.apache.org/) +- [@official@Apache Spark](https://spark.apache.org/) - [@opensource@apache/spark](https://github.com/apache/spark) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/stacked-charts@329BrtmXjXNLfi1SFfdeo.md b/src/data/roadmaps/data-analyst/content/stacked-charts@329BrtmXjXNLfi1SFfdeo.md index 52252d4dc..626482a47 100644 --- a/src/data/roadmaps/data-analyst/content/stacked-charts@329BrtmXjXNLfi1SFfdeo.md +++ b/src/data/roadmaps/data-analyst/content/stacked-charts@329BrtmXjXNLfi1SFfdeo.md @@ -4,5 +4,5 @@ A stacked chart is an essential tool for a data analyst in the field of data vis Learn more from the following resources: -- [@article@What is a stacked chart?](https://www.spotfire.com/glossary/what-is-a-stacked-chart) +- [@article@What is a Stacked Chart?](https://www.spotfire.com/glossary/what-is-a-stacked-chart) - [@article@A Complete Guide to Stacked Bar Charts](https://www.atlassian.com/data/charts/stacked-bar-chart-complete-guide) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/statistical-analysis@TeewVruErSsD4VLXcaDxp.md b/src/data/roadmaps/data-analyst/content/statistical-analysis@TeewVruErSsD4VLXcaDxp.md index 468dcbfa5..83c0a33fa 100644 --- a/src/data/roadmaps/data-analyst/content/statistical-analysis@TeewVruErSsD4VLXcaDxp.md +++ b/src/data/roadmaps/data-analyst/content/statistical-analysis@TeewVruErSsD4VLXcaDxp.md @@ -2,4 +2,7 @@ Statistical analysis is a core component of a data analyst's toolkit. As professionals dealing with vast amount of structured and unstructured data, data analysts often turn to statistical methods to extract insights and make informed decisions. The role of statistical analysis in data analytics involves gathering, reviewing, and interpreting data for various applications, enabling businesses to understand their performance, trends, and growth potential. Data analysts use a range of statistical techniques from modeling, machine learning, and data mining, to convey vital information that supports strategic company actions. -Learn more from the following resources: \ No newline at end of file +Learn more from the following resources: + +- [@article@Understanding Statistical Analysis](https://www.simplilearn.com/what-is-statistical-analysis-article) +- [@video@Statistical Analysis](https://www.youtube.com/watch?v=XjMBZE1DuBY) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/supervised-learning@FIYCkGXofKMsXmsqHSMh9.md b/src/data/roadmaps/data-analyst/content/supervised-learning@FIYCkGXofKMsXmsqHSMh9.md index 0adf84126..08fbed5fc 100644 --- a/src/data/roadmaps/data-analyst/content/supervised-learning@FIYCkGXofKMsXmsqHSMh9.md +++ b/src/data/roadmaps/data-analyst/content/supervised-learning@FIYCkGXofKMsXmsqHSMh9.md @@ -4,5 +4,5 @@ Supervised machine learning forms an integral part of the toolset for a Data Ana Learn more from the following resources: -- [@article@What is supervised learning?](https://cloud.google.com/discover/what-is-supervised-learning) +- [@article@What is Supervised Learning?](https://cloud.google.com/discover/what-is-supervised-learning) - [@article@Supervised Machine Learning](https://www.datacamp.com/blog/supervised-machine-learning) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/tableau@Sz2Y8HLbSmDjSKAJztDql.md b/src/data/roadmaps/data-analyst/content/tableau@Sz2Y8HLbSmDjSKAJztDql.md index 9a309fb99..2a83ad586 100644 --- a/src/data/roadmaps/data-analyst/content/tableau@Sz2Y8HLbSmDjSKAJztDql.md +++ b/src/data/roadmaps/data-analyst/content/tableau@Sz2Y8HLbSmDjSKAJztDql.md @@ -4,5 +4,5 @@ Tableau is a powerful data visualization tool utilized extensively by data analy Learn more from the following resources: -- [@official@Tableau Website](https://www.tableau.com/en-gb) +- [@official@Tableau](https://www.tableau.com/en-gb) - [@video@What is Tableau?](https://www.youtube.com/watch?v=NLCzpPRCc7U) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/tensorflow@FJ4Sx477FWxyDsQr0R8rl.md b/src/data/roadmaps/data-analyst/content/tensorflow@FJ4Sx477FWxyDsQr0R8rl.md index 90d31555b..1ed8ff766 100644 --- a/src/data/roadmaps/data-analyst/content/tensorflow@FJ4Sx477FWxyDsQr0R8rl.md +++ b/src/data/roadmaps/data-analyst/content/tensorflow@FJ4Sx477FWxyDsQr0R8rl.md @@ -4,5 +4,6 @@ TensorFlow, developed by Google Brain Team, has become a crucial tool in the rea Learn more from the following resources: -- [@official@Tensorflow Website](https://www.tensorflow.org/) +- [@official@Tensorflow](https://www.tensorflow.org/) +- [@official@Tensorflow Documentation](https://www.tensorflow.org/learn) - [@video@Tensorflow in 100 seconds](https://www.youtube.com/watch?v=i8NETqtGHms) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/types-of-data-analytics@Lsapbmg-eMIYJAHpV97nO.md b/src/data/roadmaps/data-analyst/content/types-of-data-analytics@Lsapbmg-eMIYJAHpV97nO.md index fa4eb4e6a..87792656b 100644 --- a/src/data/roadmaps/data-analyst/content/types-of-data-analytics@Lsapbmg-eMIYJAHpV97nO.md +++ b/src/data/roadmaps/data-analyst/content/types-of-data-analytics@Lsapbmg-eMIYJAHpV97nO.md @@ -1,20 +1,17 @@ # Introduction to Types of Data Analytics -Data Analytics has proven to be a critical part of decision-making in modern business ventures. It is responsible for discovering, interpreting, and transforming data into valuable information. Different types of data analytics look at past, present, or predictive views of business operations. +Data Analytics has proven to be a critical part of decision-making in modern business ventures. It is responsible for discovering, interpreting, and transforming data into valuable information. Different types of data analytics look at past, present, or predictive views of business operations. + +Data Analysts, as ambassadors of this domain, employ these types, to answer various questions: -Data Analysts, as ambassadors of this domain, employ these types, to answer various questions: - Descriptive Analytics *(what happened in the past?)* - Diagnostic Analytics *(why did it happened in the past?)* - Predictive Analytics *(what will happen in the future?)* - Prescriptive Analytics *(how can we make it happen?)* -Understanding these types gives data analysts the power to transform raw datasets into strategic insights. - Visit the following resources to learn more: - [@article@Data Analytics and its type](https://www.geeksforgeeks.org/data-analytics-and-its-type/) - [@article@The 4 Types of Data Analysis: Ultimate Guide](https://careerfoundry.com/en/blog/data-analytics/different-types-of-data-analysis/) - [@video@Descriptive vs Diagnostic vs Predictive vs Prescriptive Analytics: What's the Difference?](https://www.youtube.com/watch?v=QoEpC7jUb9k) - [@video@Types of Data Analytics](https://www.youtube.com/watch?v=lsZnSgxMwBA) - - diff --git a/src/data/roadmaps/data-analyst/content/unsupervised-learning@FntL9E2yVAYwIrlANDNKE.md b/src/data/roadmaps/data-analyst/content/unsupervised-learning@FntL9E2yVAYwIrlANDNKE.md index 0e549e365..0fc84ff5e 100644 --- a/src/data/roadmaps/data-analyst/content/unsupervised-learning@FntL9E2yVAYwIrlANDNKE.md +++ b/src/data/roadmaps/data-analyst/content/unsupervised-learning@FntL9E2yVAYwIrlANDNKE.md @@ -4,5 +4,5 @@ Unsupervised learning, as a fundamental aspect of Machine Learning, holds great Learn more from the following resources: -- [@article@What is unsupervised learning?](https://cloud.google.com/discover/what-is-unsupervised-learning) -- [@article@Introduction to unsupervised learning](https://www.datacamp.com/blog/introduction-to-unsupervised-learning) \ No newline at end of file +- [@article@What is Unsupervised Learning?](https://cloud.google.com/discover/what-is-unsupervised-learning) +- [@article@Introduction to Unsupervised Learning](https://www.datacamp.com/blog/introduction-to-unsupervised-learning) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/variance@ict4JkoVM-AzPbp9bDztg.md b/src/data/roadmaps/data-analyst/content/variance@ict4JkoVM-AzPbp9bDztg.md index 31b3dab16..1cba7b6e0 100644 --- a/src/data/roadmaps/data-analyst/content/variance@ict4JkoVM-AzPbp9bDztg.md +++ b/src/data/roadmaps/data-analyst/content/variance@ict4JkoVM-AzPbp9bDztg.md @@ -4,5 +4,5 @@ Data analysts heavily rely on statistical concepts to analyze and interpret data Learn more from the following resources: -- [@article@What is variance?](https://www.investopedia.com/terms/v/variance.asp) -- [@article@How to calculate variance](https://www.scribbr.co.uk/stats/variance-meaning/) \ No newline at end of file +- [@article@What is Variance?](https://www.investopedia.com/terms/v/variance.asp) +- [@article@How to Calculate Variance](https://www.scribbr.co.uk/stats/variance-meaning/) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/visualisation@jowh4CFLQiFzKaaElyCuQ.md b/src/data/roadmaps/data-analyst/content/visualisation@jowh4CFLQiFzKaaElyCuQ.md index d05387efe..0e74649a8 100644 --- a/src/data/roadmaps/data-analyst/content/visualisation@jowh4CFLQiFzKaaElyCuQ.md +++ b/src/data/roadmaps/data-analyst/content/visualisation@jowh4CFLQiFzKaaElyCuQ.md @@ -5,4 +5,4 @@ The visualization of data is an essential skill in the toolkit of every data ana Learn more from the following resources: - [@video@Data Visualization in 2024](https://www.youtube.com/watch?v=loYuxWSsLNc) -- [@article@Data visualization beginner's guide](https://www.tableau.com/en-gb/learn/articles/data-visualization) +- [@article@Data Visualization Beginner's Guide](https://www.tableau.com/en-gb/learn/articles/data-visualization) diff --git a/src/data/roadmaps/data-analyst/content/visualizing-distributions@mCUW07rx74_dUNi7OGVlj.md b/src/data/roadmaps/data-analyst/content/visualizing-distributions@mCUW07rx74_dUNi7OGVlj.md index e0fb92951..060c12c6c 100644 --- a/src/data/roadmaps/data-analyst/content/visualizing-distributions@mCUW07rx74_dUNi7OGVlj.md +++ b/src/data/roadmaps/data-analyst/content/visualizing-distributions@mCUW07rx74_dUNi7OGVlj.md @@ -1,6 +1,6 @@ # Visualising Distributions -Visualising Distributions, from a data analyst's perspective, plays a key role in understanding the overall distribution and identifying patterns within data. It aids in summarising, structuring, and plotting structured data graphically to provide essential insights. This includes using different chart types like bar graphs, histograms, and scatter plots for interval data, and pie or bar graphs for categorical data. Ultimately, the aim is to provide a straightforward and effective manner to comprehend the data's characteristics and underlying structure. A data analyst uses these visualisation techniques to make initial conclusions, detect anomalies, and decide on further analysis paths. +Visualising Distributions, from a data analyst's perspective, plays a key role in understanding the overall distribution and identifying patterns within data. It aids in summarizing, structuring, and plotting structured data graphically to provide essential insights. This includes using different chart types like bar graphs, histograms, and scatter plots for interval data, and pie or bar graphs for categorical data. Ultimately, the aim is to provide a straightforward and effective manner to comprehend the data's characteristics and underlying structure. A data analyst uses these visualisation techniques to make initial conclusions, detect anomalies, and decide on further analysis paths. Learn more from the following resources: diff --git a/src/data/roadmaps/data-analyst/content/vlookup--hlookup@9sIP-jpNjtA1JPCBjTf-H.md b/src/data/roadmaps/data-analyst/content/vlookup--hlookup@9sIP-jpNjtA1JPCBjTf-H.md index e2f920a2d..bae508007 100644 --- a/src/data/roadmaps/data-analyst/content/vlookup--hlookup@9sIP-jpNjtA1JPCBjTf-H.md +++ b/src/data/roadmaps/data-analyst/content/vlookup--hlookup@9sIP-jpNjtA1JPCBjTf-H.md @@ -1,6 +1,6 @@ # vlookup and hlookup -Data Analysts often deal with large and complex datasets that require efficient tools for data manipulation and extraction. This is where basic functions like vlookup and hlookup in Excel become extremely useful. These functions are versatile lookup and reference functions that can find specified data in a vast array, providing ease and convenience in data retrieval tasks. +Data Analysts often deal with large and complex datasets that require efficient tools for data manipulation and extraction. This is where basic functions like vlookup and hlookup in Excel become extremely useful. These functions are versatile lookup and reference functions that can find specified data in a vast array, providing ease and convenience in data retrieval tasks. The Vertical Lookup (vlookup) is used to find data in a table sorted vertically, while the Horizontal Lookup (hlookup) is used on data organized horizontally. Mastering these functions is crucial for any data analyst's toolbox, as they can dramatically speed up data access, reduce errors in data extraction, and simplify the overall process of analysis. In essence, these two functions are not just basic functions; they serve as essential tools for efficient data analysis. diff --git a/src/data/roadmaps/data-analyst/content/web-scraping@qQ64ZhSlbbWu9pP8KTE67.md b/src/data/roadmaps/data-analyst/content/web-scraping@qQ64ZhSlbbWu9pP8KTE67.md index 5a175f568..f72e0a809 100644 --- a/src/data/roadmaps/data-analyst/content/web-scraping@qQ64ZhSlbbWu9pP8KTE67.md +++ b/src/data/roadmaps/data-analyst/content/web-scraping@qQ64ZhSlbbWu9pP8KTE67.md @@ -4,5 +4,5 @@ Web scraping plays a significant role in collecting unique datasets for data ana Learn more from the following resources: -- [@article@What is web scraping what is it used for?](https://www.parsehub.com/blog/what-is-web-scraping/) -- [@video@What is web scraping?](https://www.youtube.com/watch?v=dlj_QL-ENJM) \ No newline at end of file +- [@article@What is Web Scraping & What is it used for?](https://www.parsehub.com/blog/what-is-web-scraping/) +- [@video@What is Web Scraping?](https://www.youtube.com/watch?v=dlj_QL-ENJM) \ No newline at end of file diff --git a/src/data/roadmaps/data-analyst/content/what-is-data-analytics@yCnn-NfSxIybUQ2iTuUGq.md b/src/data/roadmaps/data-analyst/content/what-is-data-analytics@yCnn-NfSxIybUQ2iTuUGq.md index cfec2d850..0977f38c8 100644 --- a/src/data/roadmaps/data-analyst/content/what-is-data-analytics@yCnn-NfSxIybUQ2iTuUGq.md +++ b/src/data/roadmaps/data-analyst/content/what-is-data-analytics@yCnn-NfSxIybUQ2iTuUGq.md @@ -1,3 +1,7 @@ # Introduction to Data Analytics -Data Analytics is a core component of a Data Analyst's role. The field involves extracting meaningful insights from raw data to drive decision-making processes. It includes a wide range of techniques and disciplines ranging from the simple data compilation to advanced algorithms and statistical analysis. As a data analyst, you are expected to understand and interpret complex digital data, such as the usage statistics of a website, the sales figures of a company, or client engagement over social media, etc. This knowledge enables data analysts to support businesses in identifying trends, making informed decisions, predicting potential outcomes - hence playing a crucial role in shaping business strategies. \ No newline at end of file +Data Analytics is a core component of a Data Analyst's role. The field involves extracting meaningful insights from raw data to drive decision-making processes. It includes a wide range of techniques and disciplines ranging from the simple data compilation to advanced algorithms and statistical analysis. As a data analyst, you are expected to understand and interpret complex digital data, such as the usage statistics of a website, the sales figures of a company, or client engagement over social media, etc. This knowledge enables data analysts to support businesses in identifying trends, making informed decisions, predicting potential outcomes - hence playing a crucial role in shaping business strategies. + +Learn more from the following resources: + +- [@article@Introduction to Data Analytics](https://www.coursera.org/learn/introduction-to-data-analytics) \ No newline at end of file