We are taught at an early age the difference between a want and a need. We all have unlimited wants, but most people aspire to live a luxurious lifestyle, take lavish vacations, dine at ritzy restaurants and drive expensive cars. Yet, we really only have a few basic needs like food, shelter and clothing. Before we can aspire to those things we’d like to have, we must first assure that our basic needs are met.
In the business of big data, basic needs and desires function in much the same manner. All organizations want to leverage their big data to validate business decisions, enhance day-to-day operations, optimize the customer experience, enable digital initiatives, gain a competitive advantage and increase revenue. Yet, any success is predicated upon organizations first satisfying their data needs.
We are now well into the age of big data. Organizations today must ensure business users are equipped with accurate, reliable data that can be easily understood from a business standpoint. To achieve that need, organizations must build a sound data governance strategy to leverage data as an enterprise asset. With the right approach, you can transform business through data governance.
In order to foster big data success and ensure data remains beneficial to the business, organizations must establish enterprise-wide data understanding from a business perspective and improve their data’s quality, usability and reliability. Data governance is about increasing the understanding of data to satisfy the requirements of everyone within an organization, including business users.
By formally aligning people, processes and technology through data governance, organizations can ensure data remains trustworthy, so business users don’t base business decisions off instinct or defective data. Business decisions based on inaccurate or incomplete data can mean missed opportunities, operational blunders, unhappy customers, decreased profitability and reputational damage.
A prosperous data governance framework should encourage a culture of open communication and collaboration among various business departments and IT resources to create an inventory of available data, assign data owners/stewards, track lineage and usage, and clearly define data, business terms, synonyms and business attributes. By providing transparency into an organization’s data landscape, business users can easily identify any risks associated with its use across various business applications, uncover analytical insights about customers, and enhance operational efficiency.
Data governance can also help score data quality levels across the data supply chain, increasing business user trust of data to improve business decisions and outcomes. Machine learning algorithms can be combined with data governance to automatically detect potential data abnormalities while simultaneously monitoring for data integrity improvement. All of this is best done though an integrated suite of data solutions to boost the effectiveness of an organization’s data governance strategy.
A comprehensive solution should provide the tools for data governance, data quality and analytics to deliver complete transparency into an organization’s data landscape. This includes the available data, its owner/steward, lineage and usage, as well as its associated definitions, synonyms and business attributes. Business users can then quickly define, track, and manage all aspects of their data assets to make crucial business decisions.
The solution should also provide data quality checks such as data profiling, consistency, conformity, completeness, timeliness, and reconciliations, in addition to the previously mentioned analytics for data integrity validation.
With complete transparency across the enterprise and complete trust in enterprise data, business users can swiftly collaborate, share knowledge across different departments, uncover critical insights, and ultimately, assure that data assets don’t just help meet the needs of an organization, but fulfill their greatest goals as well.
If you would like to learn more about developing a data governance framework and why it’s important, download the data sheet below.
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