What this years’ Dresner report means for your data-driven strategy

If your organization is like most these days, you probably have the term ‘data-driven’ tattooed on your forehead, Memento-style. In order to stay competitive, you need access to the ever-growing mountain of data at your disposal quicker than ever before. And, as you probably know, this is placing new demands on your analytical data infrastructure.

In its recently released study, Dresner Advisory Services analyzed the data infrastructure market alongside the perceptions, intentions, and realities of users.  After surveying organizations we’re pleased to report that Dresner found our data analytics platform best-in-class for product reliability, value, integrity, quality of technical support and product robustness. This makes us both a customer experience and vendor credibility leader (as shown below). As such, it isn’t surprising that, for the second consecutive year, Exasol has a perfect recommend score.

So, here’s a summary of everything the latest Dresner report tells you about what’s shaping decision making for data-driven strategies – and some initial observations for turning your data into faster, more relevant and valuable insights at speed.

The complex and changing data analytics requirements of organizations are making firms rethink their data management strategies and investments.

Selecting an ADI (analytical data infrastructure) platform is a complex and long-term decision for any organization investing in data analytics. The selection criteria needs to span a multitude of requirements, including support for diverse analytical use cases, dynamic workloads, high performance and flexibility in deployment options It also needs to ensure the data infrastructure can grow with the business and meet next-generation workloads.

The overall selection priority for a platform is performance with over 80% of respondents viewing it as critical or very important. This reflects growing demand from businesses to uncover valuable insights and get quicker access to these from their growing volumes of data. And this is true across a diverse range of use cases – including real-time analytics, advanced analytics and predictive modelling.