Unleashing Power of Data

Unleashing Power of Data | 1 [ MESSAGE FROM MD’S DESK ] When British mathematician Clive Humby declared in 2006 that “data is the new oil,” he meant that data, like oil, isn’t useful in its raw state. It needs to be refined, processed, and turned into something useful. The importance and potential of data in the current context can be ascertained by the fact that 4 out of top 5 global companies by market capitalization use data as their key raw material. With advanced technology, hyper-connected devices, Internet of Things, companies, and individuals are generating humongous amounts of data. As per the best estimates available, the world produces at least 3.3 quintillion bytes of data every day. With plenty of information all over the place, it is difficult to separate meaningful insights from the ocean of data that we have at our disposal today. That is where the ‘Power of Data’ comes into picture. Good data management is essential for organizations to derive the true potential of data and thereby stay relevant, competitive, and innovative amidst constant change. Good data management rests on five pillars viz; Standards, Strategy, Integration, Quality, and Governance. Data Standards: are rules or guidelines used to ensure that data is collected, managed, represented, and formatted in a consistent and reliable manner. The advantage of implementing right standards results in improved data quality, reliability which enables efficient and effective data analysis. Data Strategy: refers to the tools, processes that defines how tomanage, analyze, and act on the business data. Building an effective data strategy helps organization to make informed decisions based on data. Data Integration: involves combining data residing in different sources and providing users with a unified view. For example, D&B helps client to connect with D&B’s data and insights, which can be integrated seamlessly with leading CRM, MAP, ERP, and MDM platforms using pre-built out- of-the-box connectors. Data Quality: measures how well a dataset meets criteria for accuracy, completeness, validity, consistency, uniqueness, timeliness, and fitness for purpose. At D&B, we aspire to eight dimensions of data quality. Dun & Bradstreet