Survey: Jaspersoft Finds Big Data Confidence, Production Deployments on the Rise in 2014

A just-released survey from Jaspersoft shows devs and IT are becoming more confidence surrounding big data projects. The survey found respondents in 2014 better understanding how to best use technologies as well as what analytics use cases can deliver business value. IDN speaks with Jaspersoft director of product marketing Mike Boyarski.

Tags: analytics, Big Data, Hadoop, Hive, Jaspersoft, Javascript, MongoDB, survey, expert voice,

Mike Boyarski
director of product marketing

 

"We’re seeing IT finding ways to overcome obstacles to big data as they see more evidence that analytics can drive more business value"

A just-released survey from Jaspersoft shows devs and IT are becoming more confidence surrounding big data projects. The survey found respondents in 2014 better understanding how to best use technologies as well as what analytics use cases can deliver business value. IDN speaks with Jaspersoft director of product marketing Mike Boyarski.

The growing understanding of how IT and business uses can tap into business value for data is starting to create waves of broader adoption along with a stronger commitment to explore ways to simplify and innovate with production-ready solutions that focus on analytics, according to Jaspersoft execs.

“We’re seeing IT finding ways to overcome obstacles to big data as they see more evidence that analytics can drive more business value,” Jaspersoft director of product marketing Mike Boyarski told IDN.

In detail, the survey found more than one-third (36%) of respondents said they had successfully funded a big data initiative. This compares to only 15 percent is the survey last conducted in August 2012. The current survey also found broad interest in big data, with 42% of respondents reporting they were in the process of “experimenting” or conducting “general research” into big data projects.

The survey also found that the two top reasons for a company not doing big data are decreasing. In specific, respondents who said they don’t understand big data is only at 27%. This is an 89% decrease from the August 2012 survey. Having “no business justification” also fell to 20% – a 56% decrease since August 2012.

Of the 56% of respondents with big data projects, 32% are in production or in development while 23% are in the planning stage. Looking at deployment architectures, Jaspersoft’s survey found 66% are on-premises with 34% in the cloud.

The survey last year showed the tire kicking, because many developers didn’t have budget or approval [for big data]. This year, there is a big shift – from tire kicking and research we’re now seeing a lot more PoCs [proofs of concept] and faster deployment into production.”  Boyarski said.

Jaspersoft CEO Brian Gentile summed up the findings this way:

“What we’re seeing from our community is a better understanding of big data and more willingness to commit to projects. The survey suggests that experimental big data projects are on the rise while funded initiatives continue to increase as the tools and understanding of big data mature.”

Nearly 1,600 Jaspersoft members of Jaspersoft’s community participated in the survey. It is a follow up to Jaspersoft’s August 2012 survey about trends in big data.

Popular Big Data Technologies. The survey also asked what types of data respondents are using to derive analytics. It found while relational databases remain the most popular at 56%, newer data sources are coming on strong. In fact, the survey noted a huge spike in deployment of MongoDB, at 23%. Other data sources include: analytic databases (14%), Hadoop HDFS (12%) and Hive (4%)

Boyarski admitted that some might find this jump in Mongo popularity surprising.

“While Hadoop gets a lot of press and fanfare, our survey found developers are really enamored with Mongo,” he said, noting two key benefits. “Mongo is just so much easier to work with [than Hadoop] for many developers and it can collect massive amounts of information in an elegant and intuitive way,” he said.

He points to the survey to show that simplification across the lifecycle can promote wider adoption and broad adoption. “Last year, the focus was on data collection and plumbing and how to access it. This year, we’re seeing the focus shift to find ways to get analytics into a project or to even data being put directly into an application,” he added.  

Big Data Use Cases with High Business Value. As the ability to marry analytics with machine data and sensor data gets easier, IT is becoming more interested in designing data-centric apps, he said.

“Customers have apps that focus on sensor data and they’ve got it or they have components of it so they are striving to add a more analytics view – and others are looking to extend their app scope by taking data they don’t currently incorporate. We’re seeing a while new breed of app that is changing the game because it is getting so easy to capture and collect all sorts of data so quickly,” Boyarski said. 

But infusing data into apps is not limited to the latest technologies. “There are old school apps that for many years have used logs and captured other data, but IT never really know what they could do with it all. That is also changing in a major way,” he added.

The survey also asked respondents about where and how they use big data. It found these top 10 results (ranked by popularity):

  1. Customer Analytics (48%)
  2. Customer Experience Analytics (45%)
  3. Risk Analysis (37%)
  4. Threat Analysis (30%)
  5. Regulatory Compliance Analysis (28%)
  6. Campaign Optimization (26%)
  7. Location-based Targeting (23%)
  8. Fraud Analysis (22%)
  9. Brand Sentiment Analysis (16%)
  10. Product Placement Optimization (16%)

Looking to the future, to continue to drive analytics more mainstream, Boyarski said may lay in making as many parts of an analytics lifecycle as simple as possible. “There needs to be tools and technologies to make it easier for devs and architects – not just low-cost or open technologies. And, even more so there needs to be simpler and more intuitive ways for non-technical end users to use analytics for end users,” he said.

Big Data Projects Tap Wide Variety of Data Stores. The Jaspersoft survey also found a companies using a wide variety of data sources to feed their big data projects.  The survey found traditional data from CRM at financials in highest demand, but breadth of data sources are targets.

The survey noted these as a top 10 ‘most popular’ data sources.

  1. CRM (40%)
  2. Financials (38%)
  3. e-Commerce (27%)
  4. Retail POS (15%)
  5. Supply Chain Management (14%)
  6. Human Capital Management (12%)
  7. Product Lifecycle Management (11%)
  8. Support Case Logic (10%)
  9. Bug Tracking (9%)
  10.  Other (7%)

Inside Jaspersoft’s offerings for analytics, big data, and business intelligence Jaspersoft offers open source technologies that help devs design and build dashboards and reports. The company’s commercial version adds many value-added features on top, including the capability for devs to provide end users an intuitive set of self-service options where they can customize reports without the need for highly trained devs.

It also supports a wide variety of data types, including relational, transactional, unstructured and streams. It also offers native access and can combine, correlate and integrate data (via ETL, web services, APIs, virtualization and more) that avoids the need to design and implement a complex data warehouse.

The result of Jaspersoft’s open and pluggable architecture provides options and flexibility to both IT and data owners to support tasks across the design, deployment, operations and management of big data projects.  Boyarski said. “So, if a developer is working with a data set they can use native Mongo functions if they want or not, or in operations, use our in-memory cache or not, or many other choices,” he said. Big data [offerings] need to provide flexibility is one of the big take-aways for me from our latest survey.” 

Respondents to the Jaspersoft big data survey were primarily application developers – 60 % with 40% of the developers working in software, Internet and computer, or the electronics space, followed by financial services (9%), and government (8%).




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