Tag Archives: Data Services
The Architectural Scope of Data Governance
It’s important to note that I didn’t title this post “Implementing a Data Governance Architecture”. Data governance is not a technology space, tool – or architecture. As our data governance framework illustrates, tools and architecture represents but one of many facets needed to support an enterprise data governance competency. But once you’ve defined your vision and business case with a clear approach for managing the people, process and policy facets, technology can play a significant role in determining the ultimate success or failure of your data governance efforts. Complex and poorly integrated current state architectures present a significant obstacle to applying common standards for the delivery of trusted and secure data across the enterprise. Data architects play a pivotal role in enabling data governance by designing and evangelizing the data management reference architecture to support data quality and privacy requirements. In addition, these architects must recommend enabling technologies to support data governance and stewardship workflows that aid the core processes of discovery, definition, application and measurement and monitoring (Stay tuned – I’ll be sharing a lot more about these core data governance processes in a future post discussing the “Defined Processes” facet of our framework). Whatever you do, don’t fall into the all-too-common IT trap of selecting the tools before the goals, strategy and processes of data governance are in place. If you skip these steps and just try to build it, they (‘the business’) most assuredly will NOT come. (more…)
Key Characteristics of a Data Virtualization Solution (Part 3 of 3)
Data federation techniques help mitigate both the accessibility and the latency issues, but we still need to deal with the need for quality of content when employing a data virtualization approach. Within the ETL world, data inconsistencies and inaccuracies are dealt with through a separate data profiling and data quality phase. This works nicely when the data has already been dumped into a separate staging area. But with federation, not all the data is situated within a segregated staging area. Loosely-coupled integration with data quality tools may address some of the problem, but loosely-coupling data quality can’t eliminate those situations in which the inconsistencies are not immediately visible. (more…)
ANNOUNCING! The 2012 Data Virtualization Architect-to-Architect & Business Value Program
Today, agility and timely visibility are critical to the business. No wonder CIO.com, states that business intelligence (BI) will be the top technology priority for CIOs in 2012. However, is your data architecture agile enough to handle these exacting demands?
In his blog Top 10 Business Intelligence Predictions For 2012, Boris Evelson of Forrester Research, Inc., states that traditional BI approaches often fall short for the two following reasons (among many others):
- BI hasn’t fully empowered information workers, who still largely depend on IT
- BI platforms, tools and applications aren’t agile enough (more…)
What it Takes to Be a Leader in Data Virtualization!
If you haven’t already, I think you should read The Forrester Wave™: Data Virtualization, Q1 2012. For several reasons – one, to truly understand the space, and two, to understand the critical capabilities required to be a solution that solves real data integration problems.
At the very outset, let’s clearly define Data Virtualization. Simply put, Data Virtualization is foundational to Data Integration. It enables fast and direct access to the critical data and reports that the business needs and trusts. It is not to be confused with simple, traditional Data Federation. Instead, think of it as a superset which must complement existing data architectures to support BI agility, MDM and SOA. (more…)
Dodd-Frank Legislation and Structured Data Retention
The “Dodd-Frank Wall Street Reform and Consumer Protection Act” has recently been passed by the US federal government to regulate financial institutions. Per this legislation, there will be more “watchdog” agencies that will be auditing banks, lending and investment institutions to ensure compliance. As an example, there will be an Office of Financial Research within the Federal Treasury responsible for collecting and analyzing data. This legislation brings with it a higher risk of fines for non-compliance. (more…)
Seven Essential Best Practices For Data Center Consolidation
Data center consolidation is much more than physical movement of servers and infrastructure. In fact, the facility costs and power savings are just the tip of the opportunity. The biggest benefits come from using the consolidation initiative as a catalyst to rationalize the application portfolio, archive inactive data and establish one version of the truth for the data that is left. (more…)
Loose Coupling Nirvana – Canonical Techniques Part 2
To continue from my prior blog article on this topic, loose coupling between applications in an enterprise portfolio is an IT architect’s dream. If two or more applications are tightly coupled, then it becomes impossible to change or enhance one without impacting the other. Loosely coupled applications on the other hand can be enhanced independently with little or no impact on other systems. The net result is the ability to rapidly change the IT portfolio in response to business opportunities. In short, organizational agility becomes a competitive weapon. But is this dream achievable or is it only wishful thinking? (more…)
Does your Data Virtualization Solution Adapt To (Big) Data Problems
Late last year at a company all-hands meeting, the CEO of a large consumer electronics company had a serious mandate. He needed big results and fast.
“Competition is really heating up and customer churn is on the rise. I need visibility on-demand – a common view of all enterprise data or else we cannot continue to grow.” IT teams across the enterprise have been scurrying and working furiously to create a common view of CUSTOMER, PRODUCT, SALES, and INVENTORY, but the results have been incomplete, inaccurate and too slow. This is no easy task. (more…)
Customer Data Forum Off To A Great Start Featuring MDM
We launched a coast-to-coast Customer Data Forum road show with visits to Atlanta and Washington, D.C., that attracted business and IT professionals interested in using master data management (MDM) to attract and retain customers.
From the business side, our guests consisted of analysts, sales operations personnel, and business liaisons to IT, while the IT side was represented by enterprise and data architects, IT directors, and business intelligence and data warehousing professionals. In Washington, about half the audience was from public sector and government agencies. (more…)
Next-Generation Data Virtualization Series Part 2 – Characteristics
So, where have I been since my last blog? Well, I have been working on our new Architect to Architect webinar series on data virtualization, which is very exciting for me as I get to rub shoulders (virtually speaking) with hundreds of industry architects.
The interactive nature and record attendance at these webinars have made one thing very clear – data virtualization is indeed top of mind. In my last blog we discussed the concept and how data virtualization is different or a superset of traditional data federation, especially as it overcomes many limitations of the latter. Wayne Eckerson did a great job at tracking the evolution of data federation in a recent webinar and blog. (more…)
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