Cloud

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

06 Mar 2019 | Share

Dresner ADI Market Study 2019 Exasol Blog

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.

Dresner ADI Report 2019 Vendor Credibility Model Exasol

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 multiple and complex drivers for analytical data platforms

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.

80% of organizations rate performance as the deciding factor for analytics platforms

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.

55% rate scale up and out as the top-rated feature

Scale up and scale out is the top-rated ADI platform feature with over 55% of respondents viewing it as critical or very important. The report suggests that organizations require flexibility in their data architecture to support growing volumes of data but without having to sacrifice performance.

Here at Exasol, we believe our data architecture supports these requirements by supporting a large scale in-memory architecture where queries are distributed across all cluster nodes using optimized, parallel algorithms. This enables the platform to process data analytics exceptionally fast – so you can serve up insight in seconds rather than minutes and hours.

The importance of flexible deployment options

The report also found that cloud deployments are a visible trend for organizations. We believe this is driven in large part by the need to support data that’s born in the cloud plus new data analytics use cases such as data science. But as more and more data is distributed between cloud and on-premises, hybrid deployments are becoming the default approach. In our view this signals that organizations want to shift from fixed, rigid architectures to flexible ADI platforms – so they can better adapt to changing and future demand.

Our data analytics platform provides the options for storing and processing data both on-premises and across multi clouds in a hybrid deployment. At the same time, you can use virtual schemas as a conceptual framework for connecting and analyzing data sources across different data silos and repositories.

Remember, remember – in-memory is still vital for speed

In-memory data capabilities can greatly reduce the time to insight within data and delivering the performance requirements set by the business. And this is reflected in the report with more than 50% of respondents viewing in-memory as critical or very important for their ADI platform.

Our platform has been built from the ground up to support innovative in-memory algorithms, so you’re free to process large amounts of data in the main memory – giving you dramatically faster access to data.

 

Sign up for free to get the full report

I hope that’s given you a taster of where we are heading with data-driven strategies and what you need to know when choosing the right data analytics platform. But don’t just take our word for it, sign up now to download the report – free from our website.

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