How crucial is data integration for businesses?

6th Sep 2019
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Data is important for enterprises as they expand their business, but many companies are drowning in the flood of data. Storing and managing the information from data is one critical aspect and correlating that insight to the business is very important. Still many organizations take advantage of only a small portion of their data to know their business, understand demands, and enhance operations. Here is an article on why data integration solutions are necessary for businesses. 

 

This challenge is borne out in a survey of 241 IT and data decision makers by Unisphere Research, in which most respondents said that a well-documented data strategy is critical to their ability to deliver value to the business. At the same time, virtually all departments in the enterprise are demanding innovation from data, with outward-facing departments such as line-of-business owners and marketing leading the way, and inward-facing departments such as HR, warehousing, and manufacturing the least demanding. Planning is also being impacted by the need to reduce costs, eliminate data silos for better reporting, and facilitate advanced analytics leveraging technologies such as machine learning or AI. 

 

Close to half of the enterprises in the survey are aggressively planning for real time data capabilities to further enhance their data platforms. Forty-nine percent see real-time (sub-second) analytics, not just real-time ingestion, as a vital piece of their data platform planning. The biggest use cases for real-time data requirements include the timelier delivery of reports or dashboards, as well as the ability to support real-time data feeds to decision engines. Most of the data managers surveyed, 56%, cited data governance as a key concern when it comes to analytics. Data quality was cited as a concern by less than half of respondents, with 28% indicating their data quality challenges have grown since moving to the cloud. 

There are many benefits to the business from robust data integration and governance efforts. These include, of course, a more integrated view of customers and a greater ability to meet compliance requirements. Data integration and governance initiatives make data easier for users to find the information they need, while also enabling a singular terminology for data across the enterprise. Data integration and governance facilitate greater data quality and accuracy. 

The following are ways to better embrace data integration services and governance to align data to pressing business needs: 

 

• Move to DataOps. DataOps brings data and operations management into a single framework that emphasizes continuous, automation-assisted deployment to provide rapid, comprehensive, and curated data to users. Establishing a DataOps practice will help boost flexibility and agility within the data management area. 

 

• Automate as much as possible. As more data of varying formats and increasing volumes surge through the enterprise, it becomes humanly impossible to stay on top of managing and classifying it. Many vendors are developing more automated ways to address these data challenges, but enterprises need to remain a step ahead. 

 

• Build data governance into your corporate strategy. A data analytics initiative needs to be a consistent practice built into the overall corporate strategy, versus a one-off project. The data governance initiative also needs to bake many data-related activities into the day-to-day work of the enterprise. 

 

• Establish a leadership role and cross-enterprise committee. The individuals overseeing data governance—and the deployment of data analytics solutions across the enterprise—need to represent a cross-section of the business, including IT and lines-of-business leadership. There may even be a role for a chief data officer to take ownership of many of these initiatives. 

 

• Collaborate early and often. It’s important that communication between all parts of the enterprise be open, and that data governance is seen as a shared experience. This is especially important because data is coming in from many sources, is likely maintained and validated by many teams from different parts of the organization, and these sources will constantly be shifting or changing. At the same time, it’s important that the CEO and other executive leaders promote and support data governance and data analytics efforts. 

 

• Educate end users on the possibilities. It’s important to show executives, managers, and professionals the ways in which data analytics can enrich their jobs and open new ideas. Stay on top of the latest technologies. While it’s not advisable to plunge head-long into expensive technology investments which may deliver questionable value, it’s important to understand which solutions and approaches are delivering more favorable results for organizations. Promising new technologies deserve constant evaluation, and a place in the company’s ongoing data analytics strategy. 

 

• Measure, measure, and measure some more. Every business should have key performance indicators that track the progress of programs and processes. This is a key advantage for data-driven organizations, as they can quickly understand the impact of decisions and initiatives. In addition, corporate reward systems should reflect the gains made by innovation through data analytics. 

 

There will always be business areas and processes where data analytics can serve to provide greater enlightenment, and perhaps speed-to-market. There may be barriers to fulfilling these needs, such as cultural resistance or technical disconnects. Robust data integration and governance practices are essential for managing today’s data-driven enterprises. The results will be seen in greater intelligence and understanding of the environment in which the business operates. 


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