Digital Enterprise Journal (DEJ) attended Strata + Hadoop conference in New York and had a chance to discuss trends in Big Data, analytics and data management with number of vendors and user organizations. Also, we were able to append insights from the conference with findings of our Digital Transformation research and recently launched Big Data Analytics and Management survey. Here is a summary of our key takeaways.
Digital Transformation, Technology-as-a-Competitive Advantage (TaCA) and Big Data Analytics. DEJ’s Digital Transformation research shows that top performing organizations are making analytics core to their business strategy and using it as a source of competitive advantage more than any other enterprise technology. However, that message wasn’t heard very often from technology vendors at the conference. Even though there are a number of providers in this space that recognize opportunities around digital transformation, very few of them have a clear message how value proposition of their solution translates into goals of digital businesses. This is a major opportunity potentially being missed, especially because tying their value proposition to key goals for digital transformation should be easier for Big Data Analytics vendors than for providers of any other enterprise technology. Some of the vendors that came out with a clear story around digital transformation were Dell EMC, MapR, Rocana and SAP.
Role of Data Scientists. One of the key themes discussed was the value that these solutions provide in allowing Analysts and other business users easier access to data and insights and reducing the time data scientists spend on preparing data for analysis. Many conversations were even centered on how a vendor’s technology can provide value by reducing the need for hiring data scientists as they are scarce and a costly resource. This approach shows lack of understanding of the value that data science to the enterprise.
The need for data scientists will not go away just because technology will make it easier for business to access the data. On the contrary, the need for data scientists will continue to grow, not as a role that unlocks and helps translate data into insights, but as a source of innovation and differentiation in making data a source of competitive advantage.
Data science and machine learning were mentioned several times as a part of “21st century corporate literacy” and for the most part, that is true. The emergence of Big Data applications, heterogeneity of data types and sources, new opportunities around business value creation are some of the areas that make data science important in the enterprise. However, in order to unlock the potential of these opportunities, organizations need to free up resources that are allocated for discovering and preparing data.
Big Data – opportunity or a challenge? DEJ’s research shows that top performing organizations in digital transformation are more likely to see Big Data as an opportunity for creating a competitive advantage while other organizations are more inclined to report Big Data as a management challenge. As a result, top performing organizations are 1.8 times more likely to report business improvements from deploying Big Data analytics capabilities.
Seeing Big Data as a challenge is not necessarily due to a lack of management capabilities, although that does play a major role, but to the broader way of thinking about the role of different technologies in the enterprise. The major difference between top performing organizations in digital transformation and their peers is that the former group proactively searches for the edge that technologies can provide while the latter group is more likely to use the technology as a defense mechanism for dealing with market changes.
Emergence of applications. 57% of organizations in DEJ’s research reported that Big Data applications are one of their key focus areas for 2017. Application development, time-to-value from application deployments and key use cases were major themes of conversations at the conference. As organizations are looking to drive more business value from their data, this is becoming one of the key focal points in the industry and a major opportunity for differentiation.
Importance of performance. High performance and low latency were two of the major focus areas of solutions exhibited at the conference and rightfully so. Traditionally, speed of data queries have been one of the major knocks on business intelligence and analytics tools. They have been a significant barrier for new deployments. Technology vendors are putting a strong emphasis on high performance which is well aligned with user requirements as 57% of organizations in DEJ’s research reported speed of analytics as the key selection criteria.
IoT and Customer 360. In the terms of non-vertical use cases, the two most common ones were Customer 360 and IoT. DEJ’s research shows that 21% of organizations will develop capabilities for collecting data from sensors in 2017. As IoT matures as a concept, we can expect to see convergence of these two use cases which can make analytics an even more powerful tool in improving customer engagement and experience.
Collaboration. DEJ’s research shows that 44% of organizations are looking for stronger capabilities around facilitating collaboration for Big Data Analytics and it was good to see vendors focusing on that area. One of the key promises of Big Data is breaking silos and providing collaboration platforms and capabilities for business professionals and engineers so they can be aligned with that goal.
“80% data point” and messaging around it. Reducing time and resources spent on cleaning and preparing data for analysis was one of the key themes. Nearly all the vendors that we spoke with referenced “80% of time is being spent on getting data ready for analysis” quote (which, I believe” should be attributed to CrowdFlower’s 2016 survey of 80+ data scientists). However, their solutions are often taking completely different approaches in tackling this challenge and leading with this message could cause a lot of confusion with user organizations as solutions that never compete against each other may end sound the same.
However, the market is maturing and organizations are realizing that there are at least five to six technology classes that are tackling this challenge from different perspectives and many of them co-exist in user deployments. As of now, vendors are putting more emphasis on communicating value of their approach (Data Lakes, Data Cataloging, Data Wrangling, etc.), but as the market keeps growing and maturing and new vendors enter this space, vendors will need to have a stronger message about what makes their solution unique.
Analytics beyond Big Data. There are clear benefits in gaining insight from Big Data, but the value of analytics capabilities is more than applicable to organizations that are not dealing with large amounts of data. Twenty-six percent of organizations in DEJ’s research that are looking to deploy advanced analytics capabilities do not have Big Data architectures and this market segment is often overlooked. Many solution providers already have an underlining technology to address this need, but taking advantage of this opportunity will come down to the vendor’s focus, solution packaging and pricing models.
DEJ conducted briefings with 19 technology vendors that attended the conference. Here is a summary of these conversations.strata-vendor-briefings