Cisco pays Data Analysts $135,398/yr est.
Apple pays Data Analysts$131,564/yr est.
IBM pays Data Analysts $111,504/yr est.
Here are 9 Essential Tools for Data Analytics.
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Let’s dive in.
Microsoft Excel is used by data analysts to run basic queries and to create pivot tables, graphs, and charts.
Excel also features a macro programming language called Visual Basic for Applications (VBA)
Tableau is a prominent data analytics and business intelligence solution for data visualization
It simplifies raw data, dashboards, workbooks, & maps.
This makes the data accessible to everyone, allowing data analysts to share their insights and recommendations
Python is an open-source programming language used to arrange and wrangle large data sets.
Python’s built-in data-wrangling features make it a popular alternative to Excel, especially for complex data sets.
R is an open-source statistical programming language that complements python.
Data analysts love R’s output. It gives many options for communicating data analysis results.
SAS is a command-driven software program intended for sophisticated statistical analysis and data visualization
It offers a large variety of statistical methods and algorithms, as well as customized output and publication-quality graphics.
SQL is a database-accessing language.
SQL is a tool for communicating and accessing database data, which is needed to extract meaningful data for analysis.
Most large companies store their data in SQL. SQL is a must-learn for data analysts.
Data analysts and data scientists use Rapid Miner for data mining, text mining, predictive analytics, and machine learning.
Rapid Miner comes with a wide range of features including:
– data modeling
– validation
– automation
Power BI lets you visualize data and share insights throughout your organization.
Power BI is a data visualization tool like Tableau, but it’s designed for data analysts.
Power BI is a more general business intelligence tool.
FineReport is a business intelligence application used to track data trends and create reports and dashboards.
This tool is popular among data analysts and non-experts.
By the way, you don’t have to learn each and every tool.
If you want to be a Data Analyst, here I explained the fastest route.
1 – Microsoft Excel
2 – Tableau
3 – Python
4 – R
5 – SAS
6 – SQL
7 – RapidMiner
8 – Power BI
9 – FineReport
I hope you enjoyed this brief introduction.
What tools and languages are you using at work?
Please leave it in the comments section below.
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