Too Much Data, Too Few Actionable Insights…Too Late! By Pradeep Bhanot June 17, 2019 Data is the lifeblood of a modern company. It provides operations staff with visibility of company operations, marketing and product development teams with insights about what’s occurring in the marketplace and company leaders with the input they need to make informed business decisions. Unfortunately, most companies are struggling to translate their data into true business value and a sustainable competitive advantage. They have too much data, are generating too few actionable insights, and by the time they do harvest a valuable nugget, the window of opportunity to act on it has passed. Here are some of the most common challenges from business leaders regarding operational data. “We have more data than we know what to do with.” Companies have been collecting large amounts of data for years in their ERP, CRM, HR, ITSM systems and many others. With digital transformation of business processes, even more data is being generated about operational processes. Now that IoT and mobile devices are a mainstay of business, streaming data is becoming a real issue. Intuitively, companies know that data is valuable, but they continue to experience data silos and a perception that all the data they are creating is going into a black hole never to be seen again. For companies that want to develop a sustainable competitive advantage, they must start aggregating, organizing and refining their massive data stores into the real business intelligence that leads to better decisions and more efficient operations. “We are struggling to convert data into actionable insights.” Data is a raw material, not a finished good. The source of its value is a combination of quality inputs and the process of data refinement. Many company leaders forget the importance of the refinement process when aggregating, reconciling, organizing, filtering, analyzing and interpreting their data – they assume the solution for too few actionable insights is to collect more data. The key to converting data into actionable insights is having the right set of tools and a structured method for processing data through a value stream to generate progressive levels of refinement. For most companies, data moves from the source, into a data warehouse and is then distributed to users in the form of reports and dashboards. There are only 2 levels of refinement (aggregation into the warehouse and curation into reports) occurring. This isn’t enough to manage the data complexity of modern business. A 4–5 tier refinement process that includes filtering data at the source, aggregating it in an operational data warehouse, normalizing it into an enterprise data model, segmenting it into functional views and then curating it into role-based dashboards and reports will provide data consumers with better quality and actionable information insights. “By the time we harvest insights, it’s too late to act on them.” Business agility is only achievable with near real-time information insights. Batch processing of data from source systems and nightly refreshes of reports and dashboards, for example, simply isn’t sufficient to support the demands of modern businesses where minutes can represent the difference between an opportunity captured or lost and a risk becoming a crippling major incident. Digitally transformed business processes rely on real-time data to enable staff to make decisions and keep processes within the company operating smoothly. Data management solutions, such as Actian Avalanche, can help resolve the processing delay by providing a set of scalable, high-performance and cloud-based capabilities to ingest data from all your source systems in real-time and perform the necessary processing tasks to transform your raw data into actionable insights. Don’t miss another business opportunity because you have too much data and too few insights delivered too late. Visit www.actian.com/avalanche to learn more. About Pradeep Bhanot Product Marketing professional, author, father and photographer. Born in Kenya. Lived in England through disco, punk and new romance eras. Moved to California just in time for grunge. Worked with Oracle databases at Oracle Corporation for 13 years. Database Administration for mainframe IBM DB2 and its predecessor SQL/DS at British Telecom and Watson Wyatt. Worked with IBM VSAM at CA Technologies and Serena Software. Microsoft SQL Server powered solutions from 1E and BDNA.