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Hu Yoshidas blog

IT Trends for 2017: Third in a Four Part Series
Mon, 05 Dec 2016

I have divided up what I see as IT trends for 2017 into three sections. Data Center trends, Technology Trends, and IT/OT/IOT trends. In my first post in this series I gave an overview of 10 trends for 2017. My second post covered four data center trends and this post will describe four technology trends for 2017.

 

1. Bi-Modal IT

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Companies that are not born in the cloud have systems of record that they must maintain and modernize while they transform to new systems of innovation. Bimodal IT refers to having two modes of IT, each designed to develop and deliver information and technology-intensive services in its own way:

  • • Mode 1: Traditional — emphasizes safety and accuracy
  • • Mode 2: Innovation — emphasizes agility and speed

IT must be able to manage both modes and implement systems that can bridge between these two modes. While some may consider this to be a data center trend, this requires technology to integrate these two modes.

 

BI-modal IT has been publicized by Gartner as an approach to digital transformation. This approach is not new. Older establishments used this approach to transition from mainframe systems to open systems where applications had to be redesigned and re-programed for new operating and storage systems without disruption to core business services. This transition has taken a long time and many establishments still run some of their core applications on mainframes.

 

A bi-modal approach to digital transformation involves moving from structured to unstructured data and from private to public cloud services. With the right technology it can help you modernize and nurture your traditional core systems while enabling migration to new systems of innovation. Three key technologies that will help bridge between these two modes are converged solutions for bridging the infrastructure, object stores for bridging data, and integration tools for bridging the information. Converged solutions can optimize the deployment of mode 1 applications and bridge to mode 2 with orchestration and cloud ready interfaces. Data can be bridged through the use of object storage, that can support cloud interfaces, traditional structured data, and synch and share with mobile devices. Object storage can scale beyond hierarchical file systems, has extensible meta data that can ensure governance, privacy and immutability, and provide efficient, intelligent, search capability. Information that resides in mode 1 data warehouses and mode 2 unstructured data stores can be integrated in a data lake through tools like Pentaho.

 

2. Flash First

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The TCO per bit for multi-terabyte flash is already lower than hard disks based on 5 year projections for power, cooling, floor space, maintenance, and ease of management. Multi-terabyte flash eliminates those 3am calls complaining about slow response time. The cost argument against all flash is eliminated and you no longer have to argue with a user whether his data is tier 1 or 2. As a result, analyst are projecting that the revenue for flash storage will cross over the revenue for Hard disks in 2017 as the transition to Flash accelerates.

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Two factors which will create a wider price gap between flash and hard disk prices are the difference in technical roadmaps and the increasing use of flash in commodity devices. The technology to drive higher bit densities in disk drives has leveled off while flash densities continue to increase with 3D flash and Tri level cells. Prices are driven by volumes, and the volumes for hard disk are declining as PCs and other high volume commodity devices move to flash at the expense of hard disks.

 

3. A Centralized Data Hub

Data is exploding, and data is becoming more valuable as we find ways to correlate data from different sources to gain more insight, or we repurpose old data for different uses. Data can also be a liability if it is accessed by the wrong people, is exposed, or is lost, especially if we are holding that data in trust for our customers or partners. Data is our crown jewels, but how can we be good stewards of our data if we don’t know where it is, on some one’s mobile device, an application silo, an orphan copy, or somewhere in the cloud? How can we provide governance for that data without a way to prove immutability, and show the auditors who accessed it when, and how we can ensure that the data was destroyed? For these reasons, IT will be creating a centralized data hub for better management, protection and governance of their data. This centralized data hub will need to be an object store that can scale beyond the limitations of file systems, ingest data from different sources, provide secure multi-tenancy, with extensible meta data that can provide search and governance across public and private clouds and mobile devices. Scalability, security, data protection and long term retention will be major considerations. Backups will be impractical and will be eliminated through replication and versioning of updates. An additional layer of Content Intelligence, can connect and aggregate data, transforming and enriching data as it’s processed, and centralize the results for authorized users to access. Hitachi’s content platform, HCP with Hitachi Content Intelligence (HCI) can provide an object centralized data hub with seamlessly integrated cloud-file gateway, enterprise file synchronization and sharing, and big data exploration and analytics.

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4. Real time analysis, Hadoop, visualization, and predictive analytics will be a major focus

This trend will see the expanded use of in-memory data bases like SAP S/4 HANA to shorten data analysis cycles. Data streaming platforms will provide real time analysis of developing trends and analytics will be embedded in applications. Real time analytics will be connected with Hadoop analytics for further analysis and results will be stored in an object store for the possibility of future analysis. Deep learning tools have a need for historical data. Analytic tools like Pentaho will combine structured and unstructured data from different sources to provide a 360 view for analysis. Visualization tools will be designed for the business user to help make sense of the data. Predictive analytics is becoming more prevalent as businesses try to anticipate the events that affect their business. AI and robotics are beginning to enter the picture as some early adopters are using robotic call centers. Visual analytics are being used with Hitachi Visualization Systems for public safety application.

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However, no matter how fast the analysis is speeded up, it does no good if the down-stream processes and decisions do not capitalize on this analysis. Legacy systems and databases may still hinder the ability to achieve faster results unless they are aligned with in-memory analytics.

The ability to modernize core systems with technologies like in-memory computing and new analytics can prove to be highly transformational. The key is to integrate these new technologies into an overall business architecture to achieve digital transformation and deliver real business improvements.

 

You can see my Data Center trends in my previous post. My next post will focus on the last two IT trends for 2017, Smart IT the integration of IT and OT and IoT.


IT Trends for 2017: Second in Four Part Series
Tue, 29 Nov 2016

Hitachi Data Systems recently sponsored a Forbes survey of 573 C-level officers from organizations with revenues from $500 million and up across a range of industries and geographies. The purpose was to deepen our understanding of the business landscape for digital transformation, identify inhibitors to successful transformation and uncover what puts digital transformation leaders so far ahead of the pack.

Forbes digital.png

This showed that 45% of companies believe they are past the intermediate level in terms of their digital transformation. They consider themselves either advanced or leaders. The remaining 55% are either just beginning or have some technologies in place, but not on an enterprise-wide level. These numbers indicate that companies are further along in their transformation than other research we’ve seen from IDC and 451. According to Forbes, it is typical for a C-level audience to be more optimistic in their responses that those at the practitioner level. This leads me to what I see as the first four trends for 2017 which have to do with the data center.

 

Data Center Trends

1. Productivity gains will be more about people, process and business out comes.

As I mentioned in my previous blog, the explosion of new technologies over the past 10 years from smartphones to cloud computing have not resulted in a gain in productivity for most of the major countries that are considered to be technology leaders. New technologies will not result in higher productivity if we don’t change the way we use that technology. Most of us use smart phones for messaging, entertainment and pictures but that won’t increase productivity until we use it as a smart business tool. The promise of Digital transformation is to increase productivity by changing the way we use technology. Airbnb is changing the hospitality business by changing the business model to optimize the use of new technologies. Although IT has become more cost efficient over the past ten years, that has not resulted in an increase in goods and services or business outcomes.  

OECD Advance.png

Another factor that we need to realize is that all this new technology has changed the way our customers and our employees view our business. The millennial generation and now the mobile generation will be the catalyst for change in what and how we deliver our business outcomes. The C level leaders may be leading the charge for Digital Transformation, but they must focus on how to bring the workforce together and how to reskill them. I used to be very disturbed when people would leave Hitachi Data Systems for other employers, but now I realize that the workforce is more fluid today and many will choose to develop their careers by moving on and that builds a healthier stronger workforce in general. In the rush to Digital Transformation we must keep focused on people, process, and business outcomes.

 

2.The Agile Transformation of IT

Digital transformation will lead to the Agile Transformation of IT. Instead of operating in silos, of storage administrators, network administrators, server administrators, VM administrators, backup administrators, etc, taking weeks to pass change notices to one another in order to implement an application, many IT organization are adopting Agile methodologies. Business units as well as IT are under tremendous pressure to transform and that means implementing innovative new applications and platforms for all aspects of their business. From HR, marketing, development, sales, supply chain, security, compliance, to call centers. IT must become more responsive to their internal users who are more demanding, and mobile oriented, who expect the same ease of use from corporate IT as they get from their personal devices.  More IT executives are adopting Agile methodologies, working with the business units from the beginning and getting their feedback on a regular basis. Using Agile sprints of two to four weeks to replace the sequential ”waterfall” approach, failing fast, and reducing the time to deliver applications and projects to weeks rather than months. Micro services fits well with Agile and DevOps by creating re-useable services that can be developed in parallel. Containers provide more efficient use of compute services by sharing the same OS. Both micro services and containers break down traditional, monolithic applications into many small pieces of software that talk to each other to deliver the same functionality. Micro services usually run in containers which is ideal for the cloud where applications can be dialed up and down to meet service levels. IT must decide what they can do in house and what can be out sourced to contractors, managed services, or cloud. They must rethink their processes and reskill their people and their CIO must become a “business” CIO rather than a cost center manager. In Hitachi Data Systems, we have decided not to own Data Centers and now run private cloud services from a co-location facility, supporting Hitachi Data Systems and other sister Hitachi Companies. Our CIO uses Agile methodologies to implement projects with Agile teams that involve all the relevant business units.

 

3. Buying models are changing

The market is shifting away from technology asset purchasing. Because of Public cloud, most businesses are rethinking the buying model for their IT purchases. Now that they have seen the advantages of reduced costs and improved time to value of cloud and hosted cloud services, many organizations are no longer willing to establish long term commitments for assets as they have in the past where they find, three years into a five-year commitment, that the circumstances on which they based their decision three years ago are no longer valid. Buying infrastructure will be usage based acquisition through managed services, on demand or cloud.

Acquiring services will also change. Focus will be on value through outcome based pricing - If you don’t deliver you don’t get paid. Value based pricing – where you get paid on the value to the customer, perceived or estimated, rather than the cost or historical pricing. Consumption based pricing. – where the customer pays based on the resources consumed. Licensing costs will also begin to change to subscription based pricing.

 

4. Accelerating Transition to the cloud

Cloud-first strategies are the foundation for staying relevant in a fast-paced world," according to Ed Anderson, research vice president at Gartner. IT managers will be developing skills in cloud monitoring, cloud workload performance and security management, and cloud capacity management.  Instead of buying infrastructure piece parts from different vendors and knitting them together with other vendor’s management software, IT will have access to converged systems with virtualization and automation to deliver infrastructure as a service. They will begin to drive out even more cost and streamline infrastructure operations even further by combining converged solutions like Hitachi’s UCP with cloud management portals like VMware vRealize to deliver a pre-engineered approach for public, private, and hybrid cloud with a single management interface. Transition to cloud can be accelerated through services from technology partners who can plan, deploy and operationalize their cloud. Services are also available to model and profile applications and match them to an appropriate pre-engineered, pre-built service catalog within a service portal so that applications can be deployed and managed on a self-service basis. This will enable IT to avoid the long time consuming task of deploying applications after installing the cloud hardware and software.

 

 

In my next post I will be going into more detail about the following major categories of trends:

 

Technology Trends

            Bi-modal IT

            Flash First

            Centralized data hub

            Analytics

 

IT/OT/IoT

            Smart IT: The integration of IT and OT

              Growing Awareness of IoT