For decades, firms have deployed applications and BI on independent databases and warehouses, supporting custom data models, scalability, and performance while speeding delivery. It's become a nightmare to try to integrate the proliferation of data across these sources in order to deliver the unified view of business data required to support new business applications, analytics, and real-time insights. The explosion of new sources, driven by the triple-threat trends of mobile, social, and the cloud, amplified by partner data, market feeds, and machine-generated data, further aggravates the problem. Poorly integrated business data often leads to poor business decisions, reduces customer satisfaction and competitive advantage, and slows product innovation -- ultimately limiting revenue.
Forrester's latest research reveals how leading firms are coping with this explosion using data virtualization, leading us to release a major new version of our reference architecture, Information Fabric 3.0. Since Forrester invented the category of data virtualization eight years ago with the first version of information fabric, these solutions have continued to evolve. In this update, we reflect new business requirements and new technology options including big data, cloud, mobile, distributed in-memory caching, and dynamic services. Use information fabric 3.0 to inform and guide your data virtualization and integration strategy, especially where you require real-time data sharing, complex business transactions, more self-service access to data, integration of all types of data, and increased support for analytics and predictive analytics.
Information fabric 3.0 reflects significant innovation in data virtualization solutions, including:
Cisco's acquisition of Composite Software is unique compared with the ones it's done in the past. This acquisition makes networks more knowledgeable about data -- a piece that's been missing from Cisco's framework.
Today, digital information that flows through networks is not data-aware. To networks, data is just represented as bits and bytes. There's no built-in intelligence that tells the routers that some data needs higher priority when routing or needs to travel to another location before reaching its destination. The data intelligence piece is missing. This is where Composite Software comes in. Composite Software is a data virtualization company that knows what data is being used, how the data needs to be transformed and routed, and what data has higher priority.
Data virtualization deals with an abstraction layer of information from many disparate data sources -- so it can integrate with applications, databases, files, virtualization, clouds etc. Composite Software is one of the leading data virtualization companies that is often shortlisted by customers largely because of its strong product offering. It supports some of the most complex data virtualization deployments in existence -- in part because it's been active in this market as long as, or longer than, any other player. A key component in any large data virtualization implementation is the network that ensures consistent performance while accessing all of the disparate data, especially if the data is located across many servers, clouds and virtualized platforms.
Over the course of this year, I've spoken with many organizations that are continuing to expand their usage of information-as-a-service (sometimes called data services) to support new business requirements such as self-service customer portals, real-time BI, and single-version-of-the-truth. With the growing complexity of data, increasing volume of data, and exploding security challenges all driving demand, IaaS is poised to grow significantly in the coming years, especially as existing integration technologies are failing to meet these new requirements. What we see is that most organizations that have embraced an IaaS strategy over the years aren't looking back; they're continuing to expand its usage to support more requirements such as real-time data, creating data domains, improving the ability to securely deliver information, integration with unstructured data and external sources, various Web portals, and enterprise search.
Recently, my colleague Gene Leganza, who serves Enterprise Architecture Professionals, compiled the top 15 technology trends EA should watch over the next three years . One of the trends Gene highlighted is that information-as-a-service (IaaS) is finding a broader audience. I see more organizations continuing to show strong interest in IaaS, as evidenced by increasing inquiries, to help with growing data integration challenges that traditional solutions are not addressing. IaaS can significantly alter IT's approach to its data management strategy and delivers a flexible framework to support transactional, BI, and real-time data.
Here are my top predictions for 2011 related to IaaS:
I frequently get asked the question of how many databases a DBA typically manages. Over the past five years, I have interviewed hundreds of organizations on this topic, asking them about their ratios and how they improved them. Typically I find that the current industry average is 40 databases to a DBA for large enterprises ($1 billion+ in revenue), with the lowest ratio seen around eight and the highest at 275. So, why this huge variation? There are many factors that I see in customer deployments that contribute to this variation, such as the size of a database, database tools, version of databases, DBA expertise, formalization of database administration, and production versus nonproduction.
This ratio is usually limited by the total size of all databases that a DBA manages. A terabyte-sized database remains difficult to manage compared to a database that's 100 GB in size. Larger databases often require extra tuning, backup, recovery, and upgrade effort. The average database-to-DBA ratio is often constrained by the total size of the databases being managed, which tends to be around five terabytes per DBA. In other words, one DBA can effectively manage 25 databases of 200 GB each or five 1 terabyte databases. And these include production and nonproduction databases.
What are the factors that can help improve the ratio? Cloud, tools, latest DBMS version (automation), and DBMS product used - SQL Server, Oracle, DB2, MySQL, or Sybase. Although most DBMS vendors have improved on manageability over the years, based on customer feedback, Microsoft SQL Server tends to have the best ratios.
I believe that although you should try to achieve the 40:1 ratio and the 5 terabyte cap, consider establishing your own baseline based on the database inventory and DBAs and using that as the basis for improving the ratio over time.
Forrester is currently running a database management survey assessing the state of the database market. We are surveying companies across various verticals to understand the type of DBMS they use, what challenges they face and what initiatives are currently being undertaken or planned for in the coming years. We're looking at what's working and what's not, and things that you are focusing on around database management such as cloud, compression, archiving, security, and tuning.
If you are involved in some part of database management, then we'd love to hear your opinions.
All results will treated as strictly confidential and results will only ever be presented at an aggregated level.
You can take the survey here.
Thanks for your time!
Many large organizations have finally "seen the light" and are trying to figure out the best way to treat their critical data as the trusted asset it should be. As a result, master data management (MDM) strategies and the enabling architectures, organizational and governance models, methodologies, and technologies that support the delivery of MDM capabilities are…in a word…HOT! But the concept of MDM -- and the homegrown or vendor-enabled technologies that attempt to deliver that elusive "single version of truth," "golden record," or "360-degree view" -- has been around for decades in one form or another (e.g., data warehousing, BI, data quality, EII, CRM, ERP, etc. have all at one time or another promised to deliver that single version of truth in one form or another).
The current market view of MDM has matured significantly over the past 5 years, and today many organizations are on their way to successfully delivering multi-domain/multi-form master data solutions across various physical and federated architectural approaches. But the long-term evolution of the MDM concept is far from over. There remains a tremendous gap in what limited business value most MDM efforts deliver today compared to what all MDM and data management evangelists feel MDM is capable of delivering in terms of business optimization, risk mitigation, and competitive differentiation.
What will the next evolution of the MDM concept look like in the next 3, 5, and 10 years? Will the next breakthrough be one that's focused on technology enablement? How about information architecture? Data governance and stewardship? Alignment with other enterprise IT and business strategies?
Lately I have been getting quite a few inquiries on database migrations asking me about migration approaches, best practices, and tooling. Some of the reasons why companies are looking at migrations are because of staffing issues, scalability and security concerns, and cost-saving strategies. Migrations have always been complex, time consuming, and expensive, because each DBMS has proprietary data structures, data types, and SQL extensions. Once you choose a DBMS, you get locked into its platform, often creating a challenge when looking to migrate. Some companies told me that it took them more than a year to migrate some large and complex applications, which is not surprising. Although, tools and services have helped with migrations in the past, they have not been comprehensive and automated, which would make the process simple. Like an IT manager in the retail sector recently told me, "We did not want to spend a million dollars on tools and services just to save a million dollars on our database platform; it just didn't make sense."
Recently, SAP announced a definitive agreement to acquire Sybase for $5.8 billion, at $65 a share, a 44% premium over the share's three-month average price. The transaction is expected to close during the third quarter of 2010. Sybase will operate as a standalone unit under the name "Sybase, a SAP Company," and be run by Sybase's management team.
Although execs from SAP and Sybase have stressed mobility, real-time information, in-memory, and analytics benefits that come from this acquisition, the increasing pressure from Oracle cannot be undermined. Oracle's stronger focus of stack level integration and selling around applications, middleware and database, and recent acquisition of SUN has put pressure on SAP.
SAP-Sybase Deal Offers A Lot Of Synergies
SAP and Sybase offer many benefits ranging from in-memory technologies, databases, analytics, and data integration to mobility and ILM.
When preparing for our upcoming Forrester Data Management Tweet Jam (May 13th, 2-3pm ET) -"What BI is Not!"- we got together with a few of Forrester's data management and BI analysts to discuss some of today's key BI questions.
The question on the table was, "How will social media impact traditional BI?"
Here's a snapshot of what we talked about:
Jim Kobielus: (Twitter: @jameskobielus)
Over the past year, I have received numerous inquiries asking me whether third-party database tools that focus on performance and tuning, backup recovery, replication, upgrade, troubleshooting, and migration capabilities matter anymore now that leading DBMS providers such as Oracle, IBM, and Microsoft are offering improved automation and broader coverage.
I find that third-party tools complement well with native database tools in assisting DBAs, developers and operational staff in their day-to-day activities. Last year, I had the opportunity to speak to dozens of enterprises that support hundreds and thousands of databases across various DBMSes. Most enterprises reported they saw at least a 20 percent IT staff productivity when using a third-party database tool.
Third-party vendor tools remain equally important because they support:
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