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TDWI Best Practices Report | Achieving Greater Agility with Business...
The information that flows from BI, analytics, and data warehousing systems can help organizations find a decision-making balance that avoids the extremes of snap decisions and rigid processes. This...
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Agile Business Intelligence in 2013
Happy New Year to the TDWI Community! As we head into 2013, it’s clear that organizations will continue to face unpredictable economic currents, requiring better intelligence and faster decision...
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Are You Agile Enough for Big Data?
What happens if your Big Data analysis project tells you that your strategy for approaching the market is wrong? What if sentiment analysis of the tweet stream reveals that your latest product...
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The Agile Data Value Chain Series
The New Value-Cycle for Agile Data Warehousing – Part 4Copyright © 2012, Ralph Hughes, Ceregenics, Inc.In the previous portion of this blog series, Ralph described the first four of nine steps that...
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Of course Big Data will change the "Traditional" Data Warehouse
I derive great enjoyment from reading the blogs, comments and tweets about whether or not Big Data will replace the Data Warehouse. But as with most predictions, I believe there is a half-truth hidden...
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The Data Agility Tour Hits New York
In business, the word agile risks being an overused word. Like most words that get thrown into the conversation from multiple directions, its meaning gets fuzzy. It gets dropped into the conversation...
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Best Practices for DNA-based Data Warehousing
TechNewsWorld’s Peter Suciu wrote that DNA Could Become the Next Big Data Warehouse based on the Goldman et al. paper “Towards practical, high-capacity, low-maintenance information storage in...
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Data-Driven BPM: Making "Big Data" Actionable
Conversation about “big data” often leads to more questions than answers. Where does big data begin and end?Business process management (BPM) helps moves companies away from silos; big data, too, is...
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Focus on Business Relevance
Many companies are in search of the holy grail of being a more agile business. But, those same organizations are trapped in traditional decision support cycles and have fallen into a rut of “business...
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There is no such thing as "Unstructured Analysis"
There is a lot of interest in unstructured data these days. Whether this is the more “traditional” forms like video and other large bit-stream objects or things like clickstream data from the web,...
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The Status of Hadoop Implementations
The Hadoop Distributed File System (HDFS) and other Hadoop products show great promise for enabling and extending applications in BI, DW, DI, and analytics. But are user organizations actively adopting...
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Building an Agile Data Warehouse – Part 1
Data warehouses are hard to build. The goal, of course, of any data warehouse is to house all the data required to provide the business with the answers needed to run the business effectively. The...
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Shifting Big Data Focus to Outcomes, Not Technology
R Wang of Enterprise Irregulars recently argued that company’s working with Big Data need to focus on business outcomes, not technology. He writes, “The problem is most organizations start by talking...
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Building an Agile Data Warehouse – Part 2
If you accept the concepts of Agile Data Warehousing you quickly will discover that the traditional toolset (modeling tools, ETL tools, etc.) bring little to the table to advance an agile methodology....
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Big data spells new architectures
Corporate IT’s new vocation will be data integration. Mark Madsen, president of consulting firm Third Nature, will tell delegates at the London TDWI Business Intelligence (BI) Symposium next week, in...
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Hadoop Technologies in Use Today and Tomorrow
This report considers Hadoop an ecosystem of products and technologies. Note that some are more conducive to applications in BI, DW, DI, and analytics than others; and certain product combinations are...
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Big Data and the Wizard of Oz Syndrome
With big data analytics in particular, enterprises need data scientists who not only know technology, but possibly one or more of the following: statistics, econometrics, psychology and behavioral...
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Time for an Architectural Reckoning
Today’s business intelligence (BI) and data warehouse (DW) platforms are highly adapted to their environments; however, they are less suited to use outside of these environments. The same might be said...
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Parallel Parking and Other Critical Decisions
Are you confident that you have the information you need to make critical business decisions? Are you confident that the data is of sufficient quality to guide your decision down the right path? Are...
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Big Data Is Here, But Can We Avoid The Pitfalls?
Big data is hot in the Silicon Valley, but now we know that it’s officially arrived, because in early March The Wall Street Journal (WSJ) print edition ran an eight-page article on recent big data...
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Top 10 Priorities for High-Performance Data Warehousing
Data management must achieve speed and scale, to support new data types and business requirements.
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The Enterprise Brain
I was thinking about the traditional notion of data warehousing as the increasing accumulation of data, distributing information across the organization, and providing the knowledge necessary for...
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Yours, Mine and Ours
As I was straightening up my home office this weekend, I removed a stack of notes from on top of a stack of “go to” books on my desk. Three of those books belonged to “The Data Model Resource Book”...
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Big Data Management: What to Expect
Think about everything you know about data management, including its constituent disciplines for integration, quality, master data, metadata, data modeling, event processing, data warehousing,...
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The Misunderstanding of Master Data Management
Frequently, folks confuse the function and purpose of Master Data Management with Data Warehousing. I suspect the core of the problem is that when folks hear about the idea of “reference data” or a...
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Webinar: Big Challenges in Data Modeling – Modeling Governance
We invite you to join us in this monthly DATAVERSITY webinar series, “Big Challenges with Data Modeling” hosted by Karen Lopez. Join Karen and two or more expert panelists each month to discuss their...
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Agility's Growing Pains
I just finished reading a blog by Michael Fitzgerald, CIO Tough Love: Agility Demands Increasing. In his recap of the 10th annual MIT Sloan CIO Symposium, Michael rightfully warns IT Executives to...
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The MDM Hammer: Not Everything Is a Nail
You've heard the adage that if you only have a hammer, everything is a nail? It seems some companies are falling prey to that level of logic when it comes to MDM.
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BI's Next Frontier: Marketing
One of the coolest things about Business Intelligence and Analytics software is that it has applications throughout an organization. Finance can use it, sales can use it, support can use it,...
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The Ins and Outs of Big Data Governance
April Reeve of Forbes recently wrote, “What are the major drivers behind Big Data Governance? Both Big Data and Data Governance are very hot topics. Most organizations are implementing a Data...
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Iterative (and Incremental) Warehouse Development
We have often discussed the concept of using an iterative methodology when constructing a data warehouse, and have detailed the benefits of such an approach: better alignment with business needs,...
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A Good Data Warehouse Starts with a Firm Foundation
This seems so obvious that it hardly warrants mentioning, right? So why have I visited so many companies over my career where data marts, or even entire warehouses, were built using reference data from...
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Yeah, But Who Won The Race?
I just finished reading a Jim Harris blog “Chaos in the Big Data Brickyard”. When I saw the title, I thought that it must be a reference to the Indianapolis Motor Speedway, a.k.a.”The Brickyard”. I...
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An Agile Data Warehouse = A Better Night's Sleep!
General perception of the data warehouse is that it is brittle when trying to keep up with changing business requirements. If this is the case, then why was one data warehousing expert recently quoted...
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Is Your Agile Warehouse Project Stuck in Second Gear?
The first twenty-plus years of data warehouse projects yielded failure rates above fifty percent, and the waterfall methodology took much of the blame. Ironically, as Ralph Hughes points out in his...
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How (and Why) Hadoop is Changing the Data Warehousing Paradigm
Hadoop will not replace relational databases or traditional data warehouse platforms, but its superior price/performance ratio can help organizations lower costs while maintaining their existing...
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Where's My Magic Quadrant?
When I got involved with Kalido over 15 years ago, we had big plans to change the world of data warehousing, and we still do. However, one frustration we’ve had over the years is recognition from the...
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Kalido and Anchor Modeling (AM)
Someone asked me my opinion of Anchor Modeling, and I had to admit that I hadn’t really looked at it in detail. I’m not sure why — at first glance, “Almost 6th Normal Form” modified using a practical...
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The less things change, the more they stay the same
In 2012, we surveyed attendees at TDWI World Conferences regarding topics related to data warehousing: how they handle change, how long it takes to deploy new data, costs associated with supporting the...
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The marriage of Big Data and Data Warehousing
IBM published a good two part video series, where Big Data evangelist James Kobielus discusses the marriage of Big Data and Data Warehousing that is leading us toward the Hadoop Data Warehouse. In part...
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