2. Agenda
Mark Smith
CEO
Chief Research Officer
Darren Cunningham
VP Marketing, SnapLogic
• Big Data Drivers and Challenges
• Re-Thinking Big Data Integration
• SnapLogic Big Data Integration
• Next Steps
3. Poll Question #1 Results
Do you have an active big data project in your organization?
A. Yes…………………………....47%
B. No, but plan to in 2015……...20%
C. No, just researching……….....33%
4. Big Data Priorities and Drivers
Analytics and Integration are the
top two big data technologies
companies will be investing in.
said customer analytics was
the main driver for investing
in big data solutions.
+
5. The Skills Gap is an ROI Barrier
What are your primary barriers to delivering a return on your big data investments
so far?
+
6. Still a Great Deal of Uncertainty
don’t know which
distribution to use.
don’t know which
Hadoop tools to use.78% 81%
Hadoop Distribution Hadoop Tools
+
7. Poll Question #2
How do you plan to (or currently) get data into and out of Hadoop?
A) Point-to-point open source tools and/or
custom code………………………..20%
B) Our legacy integration tools….......….7%
C) New integration tools……………...13%
D) Don't know yet…………………….60%
21. Big Data Integration in a Snap
@SnapLogic
Facebook.com/SnapLogic
Plus.google.com/+SnapLogic
Learn more at!
www.SnapLogic.com!
!
Editor's Notes
Clean this up
Move speakers onto this slide.
The graphics from the infographic. No need for the “repeated header copy”
Take away the “Barrier” copy
Maybe move Hadoop Distr. And Hadoop tools to the bottom make more clear its left and right.
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As the volume of an organization’s data grows, so does the need to integrate, process and understand it. Organizations need to integrate and make business sense of data stored not only internally but in cloud computing environments and on the Internet.
Unfortunately, many of the technologies and methods being used aren’t up to the challenge. Perhaps in recognition of this inadequacy, more than three-fourths (78%) of organizations participating in our research said automating the integration of large volumes of data is important or very important. Increasingly today, to be able to extract business insights that enable people to make smart decisions they are turning to the technology known as big data.
This e-book is based on Ventana Research’s benchmark research on big data integration and is intended to provide insight into the nature and value of best practices to optimize integration processes and technology.
As the volume of an organization’s data grows, so does the need to integrate, process and understand it. Organizations need to integrate and make business sense of data stored not only internally but in cloud computing environments and on the Internet.
Unfortunately, many of the technologies and methods being used aren’t up to the challenge. Perhaps in recognition of this inadequacy, more than three-fourths (78%) of organizations participating in our research said automating the integration of large volumes of data is important or very important. Increasingly today, to be able to extract business insights that enable people to make smart decisions they are turning to the technology known as big data.
This e-book is based on Ventana Research’s benchmark research on big data integration and is intended to provide insight into the nature and value of best practices to optimize integration processes and technology.
Being able to use data-based business insights improves competitiveness. But processing larger volumes of heterogeneous data manually or using legacy tools to derive those insights is slow and risks creating errors that undermine the value of the information and confidence in it. Our research finds that more than half (55%) of organizations are only somewhat confident or not at all confident in their ability to process large volumes of data, and even more (58%) doubt their ability to process data that arrives at high velocity.
There’s also widespread dissatisfaction with the data integration technology currently in use, with most organizations finding it too slow and hard to build and maintain.
Takeaway: Using inefficient processes and tools for big data integration can undermine business effectiveness.
Evaluate the Efficiency of Your Integration Processes
Our research finds that organizations waste significant amounts of time on data integration-related tasks, particularly reviewing data for quality and consistency and preparing it for integration. These tasks are prime candidates for automation that can streamline big data integration.
Efficiency in data integration is essential to support marketplace agility. More than one-third (37%) of organizations need data hourly or daily, and another one in four need it available in real time. It therefore is critical that an organization’s big data integration capability be flexible enough to deliver cycles of processing to satisfy an array of different needs. Today fewer than half can do so.
Takeaway: Ensure that your data integration processes are both fast and flexible enough to satisfy business needs.
Examine New Approaches to Big Data Integration
Today the most used tools for managing and integrating big data are relational databases and flat files. However, only one-third of organizations are satisfied with their current technology. More than half of organizations said their current infrastructure is not fast enough or flexible enough; almost half said the technology is simply inadequate. Yet many are reluctant to move forward, saying big data technologies are too complex and cost is a barrier.
When they do, about half of organizations turn to their existing database or data integration vendor. This approach may seem simplest, but ultimately tools purpose-designed for big data will be more efficient and useful. For example, some systems now support semi-structured and unstructured data and native JavaScript Object Notation (JSON) for data interchange.
Takeaway: Big data technology is evolving, so it may not be wise to assume existing suppliers can best meet your needs. Assess carefully.
Evaluate Technology in Terms of Need
Big data integration can be a challenge, given the many sources, huge volumes and cycle times required. Choosing automation technology that can adapt to your needs today and in the future is critical.
Organizations must integrate documents and Web pages, external sources and streams of data as well as internal data from customers and transactions. The right tools can prepare all of these for integration processing. Our research shows that what matters most in selecting big data integration technology are its usability and reliability. The top three factors driving big data integration are:
business improvement initiatives (by 54%)
wider analytics and BI initiatives (46%)
improvement in the quality of business processes (40%).
Takeaway: Ensure that your evaluation of big data integration is comprehensive and considers the array of needs across business and IT.
Investigate Dedicated Technology
Our research shows that using dedicated data integration technology improves integration activities and processes. However, currently only 12 percent of organizations use dedicated technology for this purpose. In addition:
39 percent said they will begin to use it within a year
46 percent intend to use such technology but do not know when they will do so.
When you begin your investigation, look for tools that are easily used by a range of business professionals, not just IT experts. Tools being considered should be designed for big data, as our research shows that substantial numbers of organizations use or plan soon to use Hadoop (48%) and other NoSQL approaches (38%). Don’t foreclose options for your organization.
Takeaway: Use the technology best suited for big data integration and worthy of investment.
Gain Benefits that Outweigh Costs
More than half of organizations (56%) that use big data integration technology said they have improved their activities and processes by using it. They cited several benefits achieved, most often making more information available.
But your acquisition and deployment should address your organization’s needs, so pinpoint the areas of business in which investment can help. Research participants most often chose IT (57%), customer service (44%), operations (43%) and marketing (40%).
Takeaway: Know what benefits your investment will deliver by examining the impacts of investments on specific business units and IT and the resulting value.
The Cloud is Playing an Increasing Role
The business use of the cloud for applications, systems and data storage continues to grow, driven largely by cost and convenience. Our research finds that more than one-quarter of organizations have deployed big data integration software in the cloud, one-third (35%) of organizations are integrating cloud-based systems with those on-premises and nearly two-thirds (64%) said that cloud-based business applications are an important data source for their big data integration efforts – the most frequently cited external data source.
And just accessing data in traditional batch cycles isn’t the best way to utilize cloud data sources. Using cloud- and Internet-resident data can mean working with data cycling at different timing frequencies; loose coupling and late binding may be better methods for integration.
Takeaway: Assess whether your organization’s approach to the cloud is optimal for big data integration.
Big Data Requires Integration
Big data is a big deal for today’s business. Unfortunately most organizations are not well prepared to integrate the rapidly proliferating volumes of data. Poor integration cuts off timely access to actionable insights.
Every organization should develop a comprehensive strategy for managing data and turning it into actionable information – a strategy that should incorporate the integration and processing of big data and subsequent application of analytics to the data. Capable technology tools can facilitate this, making the integration smoother and faster and helping to produce better guidance.
Ventana Research believes that companies well equipped for big data integration operate more effectively. Evaluating dedicated technology designed for this new generation of requirements is a first step to increasing agility in business.
Graphic: Something about accomplishment, satisfaction to represent a positive perspective on use of technology for big data integration.
