In the digitized world, data has never been bigger, it’s expanding 24/7, and there are no signs of this slowing down. As huge volumes of data are collected, processed, stored, and archived, organizations have an opportunity to generate real business value and deliver a customer experience that is second to none. By identifying and leveraging the valuable insights that lie within their data, sound and informed decision-making can propel their business into the future. Harnessing powerful data analytics to derive these insights can be the difference between sink and swim. But what good are the analytics tools if the data they are analyzing is inaccurate in the first place?
As Melody Chien, Senior Director Analyst, Gartner clearly explains “Data quality is directly linked to the quality of decision making. Good quality data provides better leads, better understanding of customers and better customer relationships. Data quality is a competitive advantage that D&A leaders need to improve upon continuously.”
Here we take a quick look at how DMI helps improve data quality and deliver a superior customer experience.
What Does Poor-Quality Data Look Like?
Poor-quality data contains errors, inconsistencies, and duplicates, with multiple data sets created for individual customers. What’s more, stored on various systems with different software versions, the level of data integration is likely to be extremely limited, causing obstacles and slowing down business processes. A high proportion of the data may also be redundant, clogging up the live system and slowing it down. This unfavorable situation is further impeded by outdated information stored on legacy systems that can be difficult to access. It therefore comes as no surprise that organizations with poor-quality data are left trailing behind their competitors.
Improving Data Quality; Cleansing, Enrichment, and Optimization
With the right technology in place, improving the quality of company data can be a simple process. First, the data needs to be cleansed, freeing it of errors, inconsistencies, and any other anomalies that make it unreliable. By extracting all the data and documents from legacy systems and storing it on a central platform such as the JiVS Information Management Platform, automated procedures are run to verify duplicate information and to identify and eliminate any inaccuracies. The company is left with high-quality data that can then be further enriched with valuable information from other external systems before it’s all transferred to the live environment. No matter what system the company is operating, whether it be SAP S/4HANA or another ERP, with JiVS the data is continually optimized and historized on the basis of defined criteria. This keeps the operational system lean, enhancing its speed and overall performance.
A Win-Win Situation
Everyone wins when good data quality and advanced data analytics are embedded within an organization. Smart decisions are made based on reliable and accurate information that will move the business forward. And with high-quality data managed in a lean system environment with fast processing times, organizations can deliver a best-in-class customer experience and set themselves apart from the competition. Find out how DMI can help you improve the quality of your data with JiVS IMP.
*Source : https://www.gartner.com/smarterwithgartner/how-to-improve-your-data-quality
