Data Analysts Are Professionals Who Analyze Large And Complex Data Sets To Derive Insights And Make Data-Driven Decisions. They Play A Crucial Role In Helping Organizations Make Strategic Decisions By Providing Meaningful Insights And Recommendations Based On Data.
Data Analysts Use A Variety Of Tools And Software To Analyze Data, From Spreadsheet Programs Like Excel To More Advanced Software Like Python And R. In This Article, We Will Discuss Some Of The Common Tools And Software Used By Data Analysts.
Excel
Excel Is One Of The Most Commonly Used Tools By Data Analysts. It Is A Spreadsheet Programme That Allows Users To Organize, Analyse, And Visualize Data. It Can Handle Large Amounts Of Data And Has A Wide Range Of Functions And Formulas That Enable Users To Perform Complex Calculations And Analyses. Excel Also Allows Users To Create Charts And Graphs To Visualize Data And Develop Pivot Tables That Summarise Large Amounts Of Data.
SQL
A Programming Language Called Structured Query Language (SQL) Is Used To Control And Alter Data In Relational Databases. Data Analysts Use SQL To Query Databases And Extract The Data They Need To Perform Analyses. SQL Is A Powerful Tool For Data Analysts, As It Allows Them To Access And Manipulate Large Datasets Quickly And Efficiently.
Tableau
Users Can Create Interactive Visualizations And Dashboards Using The Data Visualization Tool Tableau. Data Analysts Use Tableau To Create Compelling Data Stories And Communicate Insights To Stakeholders. Tableau Also Allows Users To Connect To A Variety Of Data Sources And Perform Advanced Analytics.
Python
Python Is A Programming Language That Is Widely Used By Data Analysts. It Is A Versatile Language That Can Be Used For Data Analysis, Machine Learning, And Web Development. Python Has A Large Number Of Libraries And Frameworks That Make It Easier To Work With Data, Such As NumPy, Pandas, And Scikit-Learn.
R
R Is A Programming Language And Environment That Are Designed For Statistical Computing And Graphics. It Is A Popular Choice For Data Analysts Because Of Its Powerful Statistical Capabilities And Its Ability To Handle Large Datasets. R Has A Wide Range Of Libraries That Make It Easier To Perform Complex Analyses.