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Succeeding with Big Data: What You Need to Know

Businesses nowadays are investing greatly in big data analytics to provide better services and get more profits in return. Big data plays a “big” role in improving business decisions as it helps figure out competitive advantages over rival organizations, leading to greater revenue and more effective marketing. However, working with big data can be tricky, especially due to the sheer size and volume of data available. However, the seven tips given below can greatly help with the process:

  • Small Beginnings

There are a lot of unknowns when an organization works with data it has never handled before. There might be some confusion regarding the valuable elements of the data, the existence of quality issues, and the best metrics that can be generated. So, the time and cost required for successful big data analysis are often difficult to estimate. Thus, a small start works best. You should try and define some relatively simple analytics first that do not require much of your time or data to run.

  • Never Try to Change the Business

Succeeding with Big Data What You Need to Know_1

Understand how your business works, gauge the way people function daily within the organization and think about how big data can be used to improve the same. While this is a simple process, it also means forgetting about the more complicated technological aspects until you’re familiar with the workings of the business.

  • Understand the Scope

The more expansive the organization, the more complex its data requirements – keep this in mind while estimating the scope. You can make the process easier by speaking to the parties affected by the analysis. Discussions will help the CIO determine what resources are needed to get the job done, and also put the same in writing so no one expects anything more out of the project than what was previously discussed.

  • Focus on the Small to Make It Big

Big data analytics uses unstructured data sources that cannot be accommodated by traditional data warehouses. Moreover, the traditional data warehouses might be ill-equipped to handle the processing demands of big data. Thus, a new segment of big data technology has cropped up and is currently being used in various big data analytics environments. You need to understand that big data is composed of different, smaller datasets, and each of these datasets is capable of providing niche value. Once you bring all these datasets together, you get big value.

Understand the outcome of big data on your business as well as the analytic capabilities needed to get these outcomes before you can expect to succeed with big data. However, once you achieve that, sky’s the limit.