{"id":4932,"date":"2019-08-03T14:56:31","date_gmt":"2019-08-03T14:56:31","guid":{"rendered":"https:\/\/careerkarma.com\/blog\/?p=4932"},"modified":"2023-09-17T02:33:17","modified_gmt":"2023-09-17T09:33:17","slug":"top-tools-for-data-analysis","status":"publish","type":"post","link":"https:\/\/careerkarma.com\/blog\/top-tools-for-data-analysis\/","title":{"rendered":"Top 5 Tools for Data Analysis"},"content":{"rendered":"\n

Getting into data analytics is one of the best careers moves you can make in 2019<\/a>. We live in a world practically flooded by numbers representing consumer preferences in movies, food, books, and music, whether a person is likely to buy product B<\/em> if they bought product A<\/em>, and what the relationships between geography and political preferences are. We need analysts in order to wade through this ocean of information and determine what the data say, whether they\u2019re accurate, and how they can be used to drive business decisions. 
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And there\u2019s no indication that the growth in big data will slow down in the coming years. Whole industries like real estate and healthcare are on the brink of their own data revolutions, as entrepreneurs figure out how to digitize and work with decades of existing records. 
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If you\u2019re wanting to get into data analysis, it\u2019ll help to get clear on just what the field entails and what the common tools of the trade are. 
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What Is Data Analysis? <\/strong><\/h2>\n\n\n\n
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Learning data analysis starts with getting clear on what it is. <\/figcaption><\/figure>\n\n\n\n

The term \u2018data analyst\u2019 refers to a broad range of activities which vary by industry, project, and client. The kind of analyst work done for a social media company will likely involve A\/B testing <\/strong>which banner of a website gets more conversions, while the work done for a biomedical company will focus around tasks like determining whether the health improvements of patients taking a new drug are statistically significant. 
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But even these two examples point to a common theme. By and large, data analysts are applying the tools of statistics and probability to domain-specific problems<\/strong>. 
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Data analysts aren\u2019t exactly the same as statisticians<\/strong>, as they often don\u2019t have the same depth of theoretical knowledge. They\u2019re not the same as data scientists<\/strong> because the latter are more likely to be building machine learning models.
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Data analysts are usually responsible for ingesting data<\/strong>, visualizing<\/strong> them, performing statistical analysis<\/strong> on them, and communicating the results<\/strong>. 
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What Tools Do I Need for Data Analysis? The Top 5<\/strong><\/h2>\n\n\n\n

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With a big enough toolkit you\u2019ll always have what you need. 
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There are many, many tools that you need to master to become a data analyst<\/a>. But here are our picks for the top five best tools for the field.
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