Data analytics comes in four main flavors:
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Data analytics is the process of examining data sets to find trends and draw conclusions about the information they contain. Insights about the market and customers are essential for business success. But there have always been challenges in getting those insights. In today’s digital era, you need a data analytics solution that integrates the best of analytics and data management capabilities to access the data and analyze the information you need—when and where you need it quickly and easily.
In a constantly changing business environment, it may be hard to predict your next move. That’s where data analytics comes in. By quickly accessing data across teams and the enterprise, you can drive better decisions by getting deeper insights about:
- Who your customers are and how to reach them
- The market, including competitors
- What has happened in the past
- What’s happening now
- What the future holds for your business
There are four main types of data analytics are predictive, prescriptive, diagnostic, and descriptive.
For your initial post in this discussion:
- Research and describe the four main types of data analytics and provide an example of each one.
- Imagine that you are put in a position to build a more insight-driven organization. What would you consider for your data analytics solution? For example, you may choose a solution that optimizes all steps in your data workflow, making data and analytics processes faster. What other characteristics would you keep in mind to support all the ways that your organization uses data?
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