Advice for New Data Professionals
Whether you specialize or decide to take the “full-stack data scientist” path, here is some advice to set you up for success as a new data professional.
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Category: Data Literacy
Always Chart Your Data
Why are charts important? Why not just use summary statistics and similar outputs? This post explains one reason why you should always visualize your data.
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The Four Different Types of Analytics
There are four primary types of analytics that everyone working with data should know. Even though they all fall within the umbrella of Data Analytics, they have entirely different objectives.
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Common Data Observation Patterns and What They Mean
Identifying common data observation patterns is core data literacy skill. Anyone using data to inform their work must master these basics.
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Improving Data Literacy at Your Data-Driven Workplace
Poor workplace data literacy is pervasive. While things like data rot and data stagnation will wreak havoc on your operations, not establishing and improving data literacy at your organization will completely obstruct all your data-driven dreams.
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A Non-Analyst’s Guide to Data Assimilation and Interpretation
Workers who are not full-time data analysts still need to be skilled in data assimilation and interpretation if they’re going to use data effectively.
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What is a Spreadsheet and When Should you Use One?
Spreadsheets are convenient and powerful instruments, but you must keep a few things in mind. Get to know the limitations of spreadsheet apps like Google Sheets and Excel and where they really shine.
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