The future of big data lies in integration

Director, Adversitement

Big data—large data sets used in data analytics to make informed decisions about business and other mattersis bigger than ever, and it’s growing even bigger every day. While this creates a lot of opportunities to get to know your customers and resolve problems and pain points before they become major (or even minor) issues, it also creates new challenges, as well.

Big data has given businesses and institutions better sources for analytics, marketing, business decisions, and more, and increasing that data introduces the ability to see those pain points and correct issues before customers are even aware of them. At the same time, though, with more touch points and data points being collected from customers, processes, and employees, more and more businesses are facing the challenge of how to retrieve and analyze data faster and more easily. 

So how can businesses address this problem? The concept of big data fabric represents a fundamental change in how businesses approach data storage, fast data analytics, and streaming data to make it much easier, faster, and simpler to retrieve actionable information and increase the value that you can get from customer data. 

How is data becoming more of a challenge? 

To understand how big data fabric and other changes in the way that we view, store, and handle data and data analytics can improve business, we must first understand the most common problems and challenges that are arising due to big data’s growth. 

Until now, big data solutions and deployments have been built almost exclusively to address very specific and individualized needs. They effectively exist in their own silos, and they do not work well together. Examples of this kind of big data deployment include web clickstream data used to analyze customer information, geolocation data, and smart metering sensor data. 

Integrating individual big data deployments for better business solutions can see, as big data continues to grow, how these deployments are not scalable. If businesses continue to use these silo solutions, they will have to continue to purchase more and more tools, software, hardware, and cloud storage space simply to handle the massive amount of space involved with using so many individualized deployments. 

However, with the concept of big data fabric, integration becomes a major priority for big data solutions. Instead of working on specific and individual issues, these changes and integrations will deliver a more holistic and trustworthy view of your customers, their journeys as they interact with your brand, and their overall experiences when working with your business. 

Without the changes that come with big data fabric, you will lose valuable time in individual processes, like data ingestion, integration, security measures, storage, and more. With it, these processes will be largely unnecessary, as your data analytics solutions will not be made up of a number of random, individualized tools and deployments.

Savvy business owners around the country and around the world are already integrating their individual big data sources. This integration allows them to better focus on the most important pain points that may be detracting from their sales and/or hurting their customer experience. Through integrations like these, that link big data sources, automate data ingestion, and secure data more efficiently, you can see major improvements for your business’ data analytics, and you’ll have a scalable model that can grow into the future. 

Want to learn more about the future of big data, data analytics and how to #MakeDataSimple? Follow Ronald van Loon on Twitter and LinkedIn.