For any organization to begin meaningful analysis of its data, the data supply chain is fundamental. For better or worse, data integration and extract, transform, load (ETL) processes are analytics necessities usually owned by IT, which can make it tricky or cumbersome to get regular access to the data needed to generate business intelligence.
However, when we combine data integration and preparation processes in a self-service model, analysts have the access they need to evaluate, enrich, and process information. This maximizes the ROI on data investments regardless of top-down, bottom-up, or linear data flows.
Most enterprises have a mix-and-match environment of marketing clouds, SaaS applications and legacy IT systems. Adobe, Google, HP, IBM, Oracle, Salesforce and SAP have competing “marketing clouds” providing “all-in-one” capabilities.
In addition, there are the seemingly endless offerings of existing and new SaaS options, each contributing further data variety and complexity.
Compounding this dilemma are legacy applications, relational database management systems (RDBMS), forms, spreadsheets and other homegrown data tools.
Oh, and Big Data anyone?
The reality is that real-time or near-real-time reporting and analysis is the expectation of today’s businesses.
“The data supply chain is in transition. With competing enterprise ‘Marketing Clouds’, an abundance of SaaS tools, legacy data, big data, and the ever-growing demand for business intelligence and visualization capabilities—marketers have their hands full. Combining data integration, preparation, and management capabilities provides opportunities to add value to the enterprise,” says Bob Selfridge, Founder & CEO at TMMData.
Selfridge is scheduled to discuss these transitions in his session “Improving the Data Supply Chain,” at the 2016 Analytics Summit, hosted by ObservePoint on November 17 (now available on-demand).
Selfridge’s session explains how—through eliminating roadblocks, simplifying and providing self-service access, tools and delivery, and by leveraging data for maximum availability—the enterprise can enhance its data supply chain to allow for data integration, preparation, and augmentation in ways previously unavailable.
To view this and other sessions on-demand, visit https://www.observepoint.com/analyticssummit/.