MapR CEO – Big Data Predictions for 2015
As 2015 kicks off, John Schroeder CEO & Cofounder of MapR Technologies predicts top big data trends in this year. He sees data agility, processing data platforms, self-service, market consolidation and the rise of the enterprise architect as major developments.
- Data Agility Emerges as a Top Focus – Legacy databases and data warehouses are so expensive that database administrator (DBA) resources are required to flatten, summarize and fully structure the data. Upfront DBA costs delay access to new data sources and the rigid structure is very difficult to alter over time. The net result is that legacy databases are not agile enough to meet the needs of most organizations today. Initial Big Data projects focused on the storage of target data sources. Rather than focus on how much data is being managed, organizations will move their attention to measuring data agility. How does the ability to process and analyze data impact operations? How quickly can they adjust and respond to changes in customer preferences, market conditions, competitive actions, and the status of operations? These questions will direct the investment and scope of Big Data projects in 2015.
- Organizations Move from Data Lakes to Processing Data Platforms – During the past year, data lakes and data hubs have represented a popular first deployment for Hadoop. A data lake or data hub is a scalable infrastructure that’s both economically attractive (reduced per-terabyte cost) and designed for flexibility – it has the ability to store various forms of both structured and unstructured data. The ability to use thousands of commodity servers and store petabytes of data at less than $1,000 per terabyte per year has been a core benefit of Hadoop. In 2015, data lakes will evolve as organizations move from batch to real-time processing and integrate file-based Hadoop and database engines into their large-scale processing platforms. In other words, it’s not about large-scale storage in a data lake to support bigger queries and reports; the big trend in 2015 will be around the continuous access and processing of events and data in real time to gain constant awareness and take immediate action.
- Self-Service Big Data Goes Mainstream – In 2015, IT will embrace self-service Big Data to allow developers, data scientists and data analysts to directly conduct data exploration. Previously, IT would be required to establish centralized data structures. This is a time consuming and expensive step. Hadoop has made the enterprise comfortable with structure-on-read for some use cases. Advanced organizations will move to data bindings on execution and away from a central structure to fulfill ongoing requirements. This self service speeds organizations in their ability to leverage new data sources and respond to opportunities and threats.
- Hadoop Vendor Consolidation: New Business Models Evolve, While Others Exit the Market –Technologies mature in phases: the technology lifecycle begins with innovation and the creation of highly differentiated products, and ends when products are eventually commoditized. Edgar F. Codd created the relational database concept in 1969 with innovation leading to the Oracle IPO in 1986 and commoditization beginning with the first MySQL release in 1995. So database platform technology took over 25 years of innovation prior to any commoditization. Despite impressive global adoption at scale, Hadoop is still early in the technology maturity lifecycle with only 10 years passing since Google published the seminal MapReduce white paper. Hadoop is in the innovation phase, so vendors who mistakenly adopted “Red Hat for Hadoop” strategies are already exiting the market. The market is now 20 years into open source software (OSS) adoption that has provided tremendous value. In 2015, we’ll see the continued evolution of a new, more nuanced model of OSS to combine deep innovation with community development. The open source community is paramount for establishing standards and consensus. Competition is the accelerant transforming Hadoop from what started as a batch analytics processor to a full-featured data platform.
- Enterprise Architects Separate the Big Hype from Big Data – As organizations move quickly beyond experimentation to serious adoption in the data center, enterprise architects move front and center into the Big Data adoption path. IT leaders will be vital in determining the underlying architectures required to meet SLAs, deliver high availability, business continuity and meet mission-critical needs. In 2014 the booming ecosystem around Hadoop was celebrated with a proliferation of applications, tools and components. In 2015 the market will concentrate on the differences across platforms and the architecture required to integrate Hadoop into the data center and deliver business results.
“This is the year that organizations move Big Data deployments beyond initial batch implementations and into real time,” said Schroeder. “This will be driven by the huge strides that existing industry leaders and soon-to-be new leaders have already made by incorporating new Big Data platforms into their operations and integrating analytics with “in-flight” data to impact business as it happens.”
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