Rising Tides Analytics Blog

Big data? Here’s why you probably should be worrying about small data instead.

Posted by Rising Tides on Feb 7, 2019 9:41:17 AM

Big data? Here’s why you probably should be worrying about small data instead

Has your boss ever asked you to look into big data or has the latest tech article convinced you that big data should be your company’s focus? “Big data” is the trendy thing to talk about (and it is important), but in reality, most companies need to focus first on their small data.

This blog will examine why small data is the primary concern for most organizations and what to focus on to build a strong data analytics strategy.


Big data vs. small data

Big data continues to be a buzzword and has a number of definitions:

  • Data sets that are too large or complex for traditional data-processing application software to adequately deal with (Wikipedia)
  • Growth in the volume of structured and unstructured data, the speed at which it is created and collected, and the scope of how many data points are covered (Investopedia)
  • A process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data (Techopedia)

Big data can mean all those things and there’s a reason why it’s a popular buzzword. Big data is prevalent and important. But most organizations simply aren’t dealing with data sets at this scale.

Instead, they likely have lots of smaller data sets existing in disparate databases and programs throughout the company. Centralizing and organizing all that “small data” is the key to building an effective data strategy.

Disjointed, siloed data

So many business leaders today struggle to get the data insights they need to make strategic business decisions. A primary reason behind that struggle is that data is disjointed and siloed throughout the organization.

Revenue numbers reside in the sales department, customer utilization scores are somewhere else, and the list goes on. Likely few of these systems integrate, making all that data nearly impossible to access at a high level. The most effective data analysis can only occur when all of that data is centralized and can interact.

The foundation of a strong data strategy

So what is the solution? A properly built infrastructure is critical today to centralize and organize all the disparate data that exists in most organizations. Though some companies are moving in this direction, too many still rely on outdated data warehouses that can no longer handle the business’s vast data needs.

Here’s how to get your data where it needs to be (send this to your IT team or you may benefit from working with an outside consultant):

  1. Identify which systems of record you want to pull data from for your reporting and analytics.

  2. Work with appropriate team members to gain access to each of those systems.

  3. Choose an infrastructure model that will satisfy your current and future data analytics needs.

What else should you be focusing on?

Big data. AI. Machine learning. There are plenty of tech- and data-related buzzwords floating around today, and it can be tough to know what your organization should focus on. Because at the end of the day, all you care about is getting the insights (and the results) you need.

Grab this infographic to learn other buzzwords that you may be mistakenly investing money in, and where your organization should focus instead.

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