How to analyze and activate big data: Big data analytics (part 2)
In the previous installment, readers learned how to prepare to use big data analytics by deciding what to collect, how to collect it, how to partner for it, and how to consolidate it. In this installment, you’ll learn how to analyze and activate big data.
Using big data
Once you have big data collected and stored, you need to analyze it to uncover golden nuggets, and then automate that process to provide stakeholders with real-time insights.
Your data strategy should be based to some extent on the business objectives your organization wants to improve with big data. Then, with the data already collected and stored, you just have to run the analysis on your data. It sounds easy, but you will find numerous options and tools to choose from regarding how to analyze your data. For instance, the Big Data Landscape 2016 infographic by FirstMark Capital lists over 100 companies offering a wide range of big data analytics solutions, from machine learning to data visualization tools to analytics platforms.
With data activation, you realize that you need different answers to the same question over and over again. So, you automate systems to act on your data in real-time, or to push out information to people in real-time to help inform their actions. Data activation is the basic requirement for using big data analytics to predict behavior. Here are two examples:
- Netflix’s recommendations system works so that “an anime fan in Sweden will see recommendations based on the viewing habits of anime fans from around the world, and the same principle [applies] to every category of suggested films,” according to The Verge.
- Lattice, a business applications provider, “works so that within a system such as Salesforce.com, Microsoft Dynamics or Oracle, a salesperson is able to see their accounts ordered by the probability that they are going to close, and by clicking on the account they are also told what to mention during a call and what the trigger items are,” according to an article about predictive CRM on MyCustomer.com.
From data collection to data activation
You now have a framework for thinking about the big data possibilities for your organization from data collection to activation. As you consider your big data strategy, you may reach the conclusion that you can only make the decisions that you want to make by understanding what your prospects and customers are doing online, including the 99% of the time that they’re not on properties under your control. If so, Jumpshot can help you go straight from strategy to action.
Bottom line: Big data analytics can improve your business decisions, enhance your customer’s experience and further your businesses. This article presents a framework for organizations to use big data to reach actionable insights and increase ROI. In our next installment, we will explore how big data analytics is being applied in the technology industry, so stay tuned!