Streaming analytics, machine learning and advanced analytics were among the most talked-about themes at this year’s Strata and Hadoop World conference in New York. Information Management spoke with Jack Norris, senior vice president, data and applications, at MapR Technologies about what organizations are doing in these areas, and where the greatest challenges lie.


Information Management: What are the most common themes that you heard among conference participants?

Jack Norris: There were a few big themes, and an interesting non-theme. Topics like streams, machine learning, and advanced analytics were prevalent throughout the conference.

Many data-driven organizations are looking at event streaming architectures for creating new ways to derive business value from their data. This entails not only advantages around acting in real-time, but also data architectures that enable faster time to value.

A micro services architecture is an example of a development/deployment paradigm that leverages a streaming, or “publish-subscribe framework,” to promote rapid application development and agility. These topics all point to a greater industry focus on data platforms that can enable streams, machine learning, and a wide range of analytics.

This is why this was a particularly interesting conference for us. Organizations are recognizing that the first big challenge they need to address is identifying a platform that can cover them for all their business requirements, not only for today and the near future, but for years to come.

Conversations specifically around Apache Hadoop have dropped significantly since last year. More discussions start with requirements and goals around the use of data, versus a presumption that a particular technology is the starting point for solving business problems. These platform discussions are important, and dimensions such as performance, scalability, and reliability are top of mind.


IM: What are the most common data challenges that attendees are facing?

Norris: The most common data challenges stem from applications dictating how data is organized and stored. Data is prepared into specialized schemas to serve the application. Each application has its own dedicated silo, and the result is that you have a proliferation of silos.

The average company has hundreds of data silos throughout their organization. It’s a major challenge to deal with the many ETL processes, data duplication, and different protection schemes etc. Big Data solutions have increased these siloes which also impact data analytics.

When it comes to data analytics, the biggest challenge is how to generate analytics much faster and incorporate those into the business. In other words, move analytics from a reporting function to being able to impact the business as it happens. Organizations recognize that it’s not just how much data they have stored. Competitive advantage comes from the ability to generate the fastest and most appropriate response to changes in customer demand, competitive pressures, and market events.


IM: What are the most surprising things that you heard from attendees?

Norris: At the conference, we announced support for event-driven micro services on our converged data platform, and we believed a bit of market education was still in store for us. It was surprising to us how extensively attendees were actively considering micro services as the application paradigm they want to use for their upcoming data management initiatives.

The attendees we spoke with recognized the power of an underlying data fabric that could not only orchestrate event-driven micro services, but provide the required shared data in the same platform.


IM: How do these themes and challenges relate to your company’s market strategy this year?

Norris: Our strategy revolves around our MapR Converged Data Platform, which uniquely provides scale, speed and reliability simultaneously to enable not only mission critical but real-time processing. With MapR, organizations can provide a new class of operational applications that incorporate analytics and adjust to business events as they happen.

Supporting micro services, and making it easier to develop applications and incorporate analytics in real time is a significant enabler to organizations and a means of attracting and adding new users.


IM: What does your company view as the top data issues or challenges in 2016?

Norris: Organizations are looking more to metrics like ROI, time to value, and TCO to measure their progress. Many new data management initiatives cannot continue to be viewed as experiments like they were during the early days of big data. They need to deliver real results in a reasonable time frame.

We keep hearing about relatively low rates of success by organizations using modern technologies, but those rates don’t align with our customer success track record at all. Our customers realize significant value from their data, and continue building onto their deployments as a result of clear, measurable successes. We believe this is directly related to having the right platform, so they are able to put more focus on new use cases, and less time on maintenance, administration, and application development.

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