Hu Yoshida

2016 Will See a Greater Focus on Applications and Analytics

Blog Post created by Hu Yoshida on Dec 9, 2015

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Last week I published the 10 trends that I believe will drive IT in 2016. I also did a webtech with Greg Knieriemen our Technical Evangelist and Adrian Deluca our CTO for Asia Pacific to discuss these trends. We divided the trends into three areas, applications and analytics, infrastructure technologies, and IT leadership.

 

View the Webtech here:

https://www.hds.com/webtech/?commid=179961

 

Today I would like to expand on the first four trends, which I group under applications and analytics.

 

Most analysts are in agreement that there will be a greater focus on applications and analytics over infrastructure. This is the driver for my first 4 trends for 2016.

 

  1. 1. IT Skills Undergo Transformation

The biggest challenge for IT transformation will be the development of new IT skills. IT must develop specialist skills in areas such as cloud enablement, analytics, DevOps, mobile and business solutions.  IT people must have enough depth to contribute significantly to new solutions and capabilities. The culture of IT will need to change and be more focused on the end user than on the internal infrastructure. While infrastructure is still very important, third parties will manage more of that infrastructure, and IT’s focus will be on the policies and procedures to monitor and manage these third parties, whether it is on site, hosted, or in the cloud.  This transformation of IT skills will require the commitment of both business and IT leaders to provide the time and tools to enable their staff to acquire new skills. IT people must take every opportunity to upgrade their skills.

 

  1. 2. DevOps Adoption Accelerates Application Delivery

DevOps is the practice of operations and development engineers working together throughout the design, development, test, and delivery of application software. This is facilitated by technologies like virtualization, containers, converged solutions, software defined, open stack, cloud, and automation tools. Also fueling this adoption are survey results that show DevOps practices deliver measurable benefits. Puppet Labs, an IT Automation Software company, has been conducting yearly surveys on the state of DevOps. In their 2015 State of DevOps Report they surveyed over 20,000 tech professionals worldwide.

 

“We validated that high-performing IT organizations deploy code 30 times more frequently than their peers with 50% fewer failures. And for the first time, we showed that IT really does matter to the business: Companies with high IT performance are twice as likely to exceed their profitability, market share and productivity goals.”

 

  1. 3. Data Warehouses Transition Into Data Lakes

Big data analytics involves the processing of large amounts of heterogeneous data derived from multiple sources and across multiple knowledge domains. Data lakes enable this by bringing together data sources in their original state, which can then be analyzed by applications that are brought to the data. They must also be able to incorporate existing data warehouses to leverage the investments that have already been made.

The term “data lake” was coined by James Dixon, of Pentaho, which is a Hitachi Data Systems company. Dixon used the term initially to convey the limitations of traditional data marts. He wrote: "If you think of a datamart as a store of bottled water – cleansed and packaged and structured for easy consumption – the data lake is a large body of water in a more natural state. The contents of the data lake stream in from a source to fill the lake, and various users of the lake can come to examine, dive in, or take samples." Dixon identified 2 shortcomings of data marts: "Only a subset of the attributes are examined, so only pre-determined questions can be answered." and "The data is aggregated so visibility into the lowest levels is lost." With the use of scale out compute/storage nodes, data lakes enable users to bring applications and analytics to the data rather than moving data to the applications. This avoids the time and expense of extracting data from a database into a data warehouses, and then extracting it again into datamarts.

 

  1. 4. IT Takes Control of Provisioning Analytics Platforms

Business leaders will look to IT to make investments in analytics platforms, acknowledging the fact that IT has a better understanding of security, data privacy, integration and the service level requirements of the business. This will reverse the shadow IT trend of business units acquiring their own analytics platforms and tools and creating their own data silos. While it is easy today for business units to acquire analytics tools and run them out side of IT, this lacks the governance that IT provides. CEO’s like John Cryan of Deutsche Bank is one of many business leaders who are looking to modernize IT in order to get the most out of their data and improve performance.

 

In my next two posts I will expand on the rest of the IT trends for 2016.

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