Email: info@hitechito.com Voice (India) : +91-794-000-3266
Building an Intelligent Organization - BI, UDM and Data Analytics Strategies By: Chirag Shivalker
What should a good unified data management and analytics strategy look like? Here we explain it in three critical steps.
1
Today in the age of digitization and information exchange, we are knowingly or unknowingly contributing to an infinite pool of data. In most of the organizations, this ever increasing data is managed in isolated silos. This data is processed using various tools for data quality, data integration, information governance, master data and metadata management, B2B data exchange, content management etc, to name a few. Data management, processing and analysis, to derive meaningful information that organizations can use to take informed decisions for the best business outcomes, are a growing trend. This is exactly, why organizations are increasingly embracing unified data management practices that help coordinate teams and integrate tools. Unified data management (UDM) also popularly known as enterprise data management or enterprise information management is used to achieve strategic and data driven business objectives such as business intelligence. The field of big data, data analytics and hence BI- i.e. business intelligence, has become much more main stream in the recent years, and is predicted to grow at a bullish rate. As a result, organizations are looking for people who can collect all this unstructured data convert it into structured data or information and provide organizations with business insight. These professionals are called data scientists or business intelligence developers. It is predicted that by 2018, there will be nearly 4 million positions in US alone for such data scientists who can deal with any work related to big data, data analytics, BI and UDM.
What should a good unified data management and analytics strategy look like? Here we explain it in three critical steps: 1) Addressing your Analytics and Operational needs: Today the volumes of unstructured data are growing at a great speed and the IT environment has become highly complex, as a result the costs and risks for projects have also increased. This necessitates information integration across legacy and distributed systems. New and effective methods that support efficient collection consolidation and provide access to mission critical data in real time for analytical activities lie at the core. Data is a valued asset for an organization, and decision making for better business outcomes, solely depends on how this valued asset – i.e. data – no matter from where it originates or in what format it is available, is streamlined and leveraged to drive improved performance and gain a competitive edge.
2
2) Efficient Data Quality Management: Availability of consistent and good quality information is crucial to ensure that all the processes get executed seamlessly. Integration of new systems with the existing infrastructure in a seamless manner while maintaining the data integrity to deliver efficient and accurate services is crucial. This requirement can be fulfilled by enabling a data integration solution that has data quality management capabilities built into it. This ensures that the kind of sync and integrity requirement is maintained; as a result information sharing amongst internal and external resources becomes more organized and secure. Before any data is unified with the existing enterprise data, it needs to be analyzed and validated for its quality and accuracy. This can be done by embedding a data quality firewall in the integration process. As a result the enterprise data always remains clean and useful. 3) Business Critical Data should be amalgamated for Single View: The last but the most critical step that helps deliver superior analytics is standardizing costs, risk mitigation and revenue and mastering this mission critical data into a single view. For instance, if an online retailer has sales data from different sources across multiple systems and applications, then this data needs to be mastered and unified in order to derive accurate analytics and information that supports the company to make decisions that promote business growth. Effective data management and structuring lies at the top of the pyramid of Business Intelligence (BI). The rise of business intelligence and the willingness of companies and organizations to bring data into decisions can definitely transform businesses across the world and help them gain an edge over their competitors and drive business growth. Article Source: http://goo.gl/MRLwe1#Building-an-Intelligent-Organization
3