Organizations in the petroleum industry are no strangers to large volumes of data. With the right technology solutions, these companies can move beyond traditional real-time monitoring to more agile real-time prediction. By rapidly analyzing incoming technical and business data—and applying that information to complex models in real time—they can generate tactical insights that help increase drilling and production performance while preventing problems. By quickly searching and analyzing a large volume and variety of competitive intelligence, such as news about competitive mergers, acquisitions or new investments, they can substantially improve strategic decision making.
Using IBM Security Intelligence with Big Data, security organizations can analyze more data more flexibly, and gain more accurate results. By analyzing structured, enriched security data alongside unstructured data from across the enterprise, the IBM solution helps find malicious activity hidden deep in the masses of an organization’s data, for advanced threat and risk detection.
Technology in the energy and utilities industry is becoming increasingly advanced, including that of smart meters and smart grids. Although the evolution of these technologies provides companies with tremendous business insight, they also generate unprecedented data volume, speed and complexity. This white paper examines the business requirements, technical challenges and IBM solutions for a variety of data-driven decision-making and planning imperatives for companies in this industry.
With a wealth of information readily available online, consumers are now better able to compare products, services and prices—even as they shop in physical stores. If retailers succeed in addressing the challenges of “big data,” they can use this data to generate valuable insights for personalizing marketing and improving the effectiveness of marketing campaigns, optimizing assortment and merchandising decisions, and removing inefficiencies in distribution and operations.
Big data offers organizations new ways to use enterprise data to deepen business insights and extend competitive advantage. Yet many companies are unsure of where to start. An IBM® Readiness Assessment for big data is designed to help. Available at no charge in half-day, single-day or multiday sessions, a Readiness Assessment for big data brings together your IT and line-of-business managers with IBM big data experts in a highly interactive engagement that will help initiate your big data operations.
IBM InfoSphere Optim is a leader in Gartner Inc's Magic Quadrant for Data Masking Technology. InfoSphere Optim received the best ranking in the ability to execute and completeness of vision categories compared to competitors. Gartner reports that data masking should be mandatory for enterprises using copies of sensitive production data for application development, analytics or training.
How do businesses address the challenges of growing volume and variety of data? How can I introduce new data sources and workloads into my architecture? How do I achieve better time to value and agility in my infrastructure?
If you're wrestling with these and other related questions, I recommend you look into a newly released paper called, “Architecting a Big Data Platform for Analytics” by industry analyst Mike Ferguson of Intelligent Business Strategies. In this paper, Ferguson explores the requirements and considerations for building an enterprise big data analytic ecosystem. Considering more than 20 years of market maturity, the paper addresses the challenges facing businesses with multiple data warehouses and data marts.