Big Data, Bigger Impact

Ken Rudin gave a great presentation on Big Data as keynote speaker at TDWI World Conference, happened early this month in Chicago, IL.  Ken is the Director of Analytics at Facebook, where he’s focused on ensuring that analytics is a key strategic asset for Facebook. He’s responsible for leveraging Facebook’s massive analytics platform to generate high-impact insights that optimize both the Facebook user experience and Facebook’s overall business.

Watch and enjoy!

YouTube: http://www.youtube.com/watch?v=xKrw2TKfj4w

The BI Year in Review

The Data Warehousing Institute (TDWI) published in December a retrospective called The BI Year in Review. The retrospective, written by Stephen Swoyer, is a well-detailed article about what happened in BI area in 2011. Below is a summary of the article:

Interacting with BI Apps and the Impact of Mobile Computing

In 2011, the evolving BI usage paradigm officially moved beyond the desktop LCD: smartphones and tablets aren’t simply being supported, they’re being actively cultivated. One upshot of this is that nearly every purveyor of BI client offerings has a mobile or tablet strategy that tends to mix support for mobile devices of all kinds -- chiefly via HTML5-based Web applications -- and device-specific support, usually (but not always) limited to Apple Inc.’s iOS devices.

For now, let’s just say that the way in which we interact with BI is going to change. Drastically. After all, it already has changed, and what we expect from BI applications has changed, too. Even before 2011, innovation in BI had already outstripped the bread-and-butter contexts in which business intelligence had been served up for decades. These old-school interfaces -- viz., spreadsheets, with their cells, rows, and columns; static charts, diagrams, scorecards, and so on -- haven’t so much been replaced as been supplemented: enriched.

Advanced Social Studies

The socialization of BI has been inexorable. Not fast. Not slow. Inexorable. The trend this year might be called Creeping Socialization. It was a phenomenon in which at least a dozen BI vendors kicked off efforts to retrofit their offerings with social media (or social media-like) capabilities.

However, 2011 wasn’t the year in which BI first became social. Nor was it the year in which BI completed its social makeover. It was, instead, the first full year in which the industry gravitated, inexorably and irrevocably, toward social BI.

No Room for Squares

BI usage models aren’t the only things changing. This year brought a reconfiguration of the industry pecking order, with the emergence of several small or upstart competitors and the reinvention -- or reorientation -- of a number of established players, too. Several vendors say they’re exploiting gaps in the existing BI marketplace: i.e., segments, pain points, or use cases that they say are ill-served by existing offerings -- or by existing usage paradigms.

Changes in Attitude

Established players repositioned themselves to exploit opportunities in the ever-evolving data integration (DI) and data virtualization (DV) marketplace.

Maximum Consumption

Few industries have produced as much acquisition activity as the BI space over the last decade. This year, consolidation in the analytic database arena -- long-anticipated, and, starting in 2010, partially realized -- continued apace, with Hewlett-Packard Co. (HP) gobbling up columnar database powerhouse Vertica Inc. Not to be outdone, Teradata Inc. acquired analytic database highflier Aster Data Inc. Along with the former Greenplum Software Inc., which was acquired last year by EMC Corp., Aster was one of the first two analytic database entrants to bring a native implementation of MapReduce to market. There are still plenty of extant analytic database competitors, however. Veterans Infobright, Kognitio, and ParAccel, along with newer entrants including Algebraix Data Corp. and Actian Corp. (the former Ingres Corp.), seem determined to keep things interesting.

Also this year, Oracle Corp. ponied up $1 billion to acquire Endeca Corp., an established vendor that specialized in faceted search. Although search was indisputably Endeca’s bread and butter -- its technology is used to power at least half of the Top 100 e-commerce sites -- the company believed it could make a big splash in the BI market, too.

A Torrent of Tablets

Enterprise IT organizations are proceeding apace with tablet computing adoption efforts: many are already using iPads (or, less frequently, competitive tablet offerings) in production, while most are at least mulling tablet strategies.

A study from software development researcher Evans Data Corp. found that a majority of mobile developers are focusing on Web apps instead of native apps -- in spite of the dominance of the iPad or (in the small-form-factor mobile arena) the iOS or Android platforms.

This is a good retrospective on the BI area in 2011. The BI scenario is changing dramatically, with new concepts, technologies and tools. I believe that 2012 will be no different.

Strategies for Creating a High-Performance BI Team

Wayne Eckerson writes a good blog in The Data Warehousing Institute (TDWI)'s website, where he publishes posts about BI issues. Recently, he published two great posts regarding to create high-performance BI Team, entitled Strategies for Creating a High-Performance BI Team and Attracting and Retaining Top BI Professionals. In my opinion, create and maintain a high-performance BI Team is one of the most important steps to develop a successful BI initiative.

In the article Strategies for Creating a High-Performance BI Team, he defined seven guidelines that can help to create a high-performance BI team that delivers outstanding value to your organization:

1. Recruit the best people. The companies shouldn’t hire people just because they know a specific tool or programming language or have previous experience managing a specific task, such as quality assurance. If you need specialists like that, it’s better to outsource such positions to a low-cost provider on a short-term contractual basis. Although you should demand certain level of technical competency and know-how, you ultimately want people who fundamentally believe that BI can have a transformative effect on the business and possess the business acumen and technical capabilities to make that happen.

2. Create multi-disciplinary teams. The key to remaining nimble and agile as your BI team grows is to recreate the small, multi-disciplinary teams from your early stage BI initiative. Assign three to five people responsibility for delivering an entire BI solution from source to report. Train them in agile development techniques so they work iteratively with the business to deliver solutions quickly. With multiple, multidisciplinary teams, you may need to reset the architecture once in awhile to align what teams are building on the ground, but this tradeoff is worth it. Multi-disciplinary teams work collaboratively and quickly to find optimal solutions to critical problems, such as whether to code rules in a report, the data model, or the ETL layer. They also provide staff more leadership opportunities and avenues for learning new skills and development techniques.

3. Establish BI Governance. Once a BI team has achieved some quick wins, it needs to recruit the business to run the BI program while it assumes a supportive role. The key indicator of the health of a BI program is the degree to which the business assumes responsibility for its long-term success. Such commitment is expressed in a formal BI governance program.

Most BI governance programs consist of two steering committees that meet regularly to manage the BI initiative. An executive steering committee comprised of BI sponsors from multiple departments meets quarterly to review the BI roadmap, prioritize projects, and secure funding. Second, a working committee comprised of business analysts (i.e., subject matter experts who are intensive consumers of data) meets weekly or monthly to define the BI roadmap, hash out DW definitions and subject areas, suggest enhancements, and select products. The job of the BI team is to support the two BI governance committees in a reciprocal, trusting relationship.

4. Find Purple People. The key to making BI governance programs work is recruiting people who can straddle the worlds of business and information technology (IT). These people are neither blue (i.e., business) nor red (i.e., IT) but a combination of both. These so-called purple people can speak both the language of business and data, making them perfect intermediaries between the two groups. Astute BI directors are always looking for potential purple people to recruit to their teams. Purple people often hail from the business side where they’ve served as a business analyst or a lieutenant to a BI sponsor.

5. Aspire to Becoming a Solutions Provider. The best BI teams aren’t content simply to provision data. BI directors know that if the business is to reap the full value of the BI resource, their teams have to get involved in delivering BI solutions.

High-performance BI teams work with each department to build a set of standard interactive reports or dashboards that meet 60% to 80% of the needs of casual users in the department. They then train and support each department’s “Super Users” -- tech-savvy business users or business analysts--to use self-service BI tools to create ad hoc reports on behalf of the casual users in the department, meeting the remaining 20% to 40% of their information requirements.

6. Give Your BI Team a Name. A name is a powerful thing that communicates meaning and influences perception. Most business people don’t know what business intelligence or analytics is (or may have faulty notions or ideas that don’t conform with the mission of your team.) So spend time considering appropriate names that clearly communicate what your group does and why it’s important to the business.

7. Position BI within an Information Management Department. The BI team should be organized within a larger information management (IM) department that is separate from IT and reports directly to the CIO or COO. The IM department is responsible for all information-driven applications that support the business. These may include: data warehousing, business intelligence, performance management, advanced analytics, spatial analytics, customer management, and master data management.

Attracting and Retaining Top BI Professionals

In the article Attracting and Retaining Top BI Professionals, he wrote that to create high-performance BI teams, we need to attract the right people, and there are a couple of ways to do this: Skills Versus Qualities, and Performance-based Hiring.

Skills Versus Qualities

Inner Drive. First, don’t just hire people to fill technical slots. Yes, you should demand a certain level of technical competence. The bottom line is that you shouldn’t hire technical specialists whose skills may become obsolete tomorrow if your environment changes. Hire people who have inner drive and can reinvent themselves on a regular basis to meet the future challenges your team will face. If you need pure technical specialists, consider outsourcing or contracting people to fill these roles.

Think Big. To attract the right people, it’s important to set ambitious goals. A big vision and stretch targets will attract ambitious people who seek new challenges and opportunities and discourage risk-adverse folks who simply want a “job” and a company to “take care” of them. One way to think big is to run the BI group like a business. Create mission, vision, and values statements for your team and make sure they align with the strategic objectives of your organization. Put people in leadership positions, delegate decision making, and hold them accountable for results.

Performance-based Hiring

Proactive Job Descriptions. We spend a lot of time measuring performance after we hire people, but we need to inject performance measures into the hiring process itself. To do this, write proactive job descriptions that contain a mission statement, a series of measurable outcomes, and the requisite skills and experience needed to achieve the outcomes. If done right, a proactive job description helps prospective team members know exactly what they are getting into. They know specific goals they have to achieve and when they have to achieve them. A proactive job description helps them evaluate honestly whether they have what it takes to do the job.

Where are they? So where do you find these self-actuated people? For example, you can find on online forums, such as TDWI's LinkedIn group, and on Twitter. You can assess the quality of advice they offer.

Retaining the Right People

Finally, to retain your high-performance team, you need to understand what makes BI professionals tick. Salary is always a key factor, but not the most important one. BI professionals want new challenges and opportunities to expand their knowledge and skills. One way to retain valuable team members is to create small teams responsible for delivering complete solutions. This gives team members exposure to all technologies and skills needed to meet business needs and also gives them ample face time with the business folks who use the solution. BI professionals are more motivated when they understand how their activities contribute to the organization’s overall success. Another retention technique is to give people opportunities to exercise their leadership skills. For instance, assign your rising stars to lead small, multidisciplinary teams where they define the strategy, execute the plans, and report their progress to the team as a whole.

Wayne Eckerson defined very well in which their articles the way to create a High-Performance BI Team. Certainly companies that create their BI teams following those guidelines will have a great chance of developing a successful BI program.

Wayne Eckerson is the author of the book Performance Dashboards: Measuring, Monitoring, and Managing Your Business (I wrote a book review on this book)

Rethinking the role of BI

Increasingly, the companies have questioned the importance of the BI teams in the delivery of value to business and also to be more effective and strategic to organizations. Wayne Eckerson wrote a great post on the role of BI in his blog at The Data Warehousing Institute (TDWI), entitled Evolving Your BI Team from a Data Provider to a Solutions Provider. He commented about a Jill Dyche's presentation at TDWI’s BI Executive Summit, where she explained that BI teams can either serve as "data providers" or "solutions providers." Data providers focus on delivering data in the form of data warehouses, data marts, cubes, and semantic layers that can be used by BI developers in the business units to create reports and analytic applications. Solutions providers, on the other hand, go one step further, by working hand-in-hand with the divisions to develop BI solutions.

Eckerson believes that BI teams must evolve into the role of solutions provider if they want to succeed long term. They must interface directly with the business, serving as a strategic partner that advises the business on how to leverage data and BI capabilities to solve business problems and capitalize on business opportunities.

He wrote that historically, many BI teams become data providers by default because business units already have reporting and analysis capabilities, which they've developed over the years in the absence of corporate support. These business units are loathe to turn over responsibility for BI development to a nascent corporate BI group that doesn't know its business and wants to impose corporate standards for architecture, semantics, and data processing.

However, this separation of powers fails to deliver value, he commented. The business units lose skilled report developers, and they don’t follow systematic procedures for gathering requirements, managing projects, and developing software solutions. They end up deploying multiple tools, embedding logic into reports, and spawning multiple, inconsistent views of information. Most of all, they don’t recognize the data resources available to them, and they lack the knowledge and skills to translate data into robust solutions using new and emerging BI technologies and techniques, such as OLAP cubes, in-memory visualization, agile methods, dashboard, scorecards, and predictive analytics.

A corporate BI team needs to rethink its mission and the way it's organized. It needs to actively engage with the business and take some direct responsibility for delivering business solutions. To provide solutions assistance without adding budget, it will break down intra-organizational walls and cross-train specialists to serve on cross-functional project teams that deliver an entire solution from A to Z. The BI team will become more productive and before long eliminate the project backlog.

He commented about some successful cases where the companies have a high performance BI team. In one of them, for example, the BI is housed in an Information Management (IM) organization that reports to the CIO and is separate from the IT organization. The IM group consists of three subgroups: 1) the Data Management group, a data integration team that handles ETL work and data warehouse administration 2) the Information Delivery group, a BI and Performance Management team which purchases, installs, and manages BI and PM tools, provides training and solutions using reporting, OLAP, and predictive analytics capabilities; and 3) the IM Architecture group, that builds and maintains the IM architecture, which consists of the enterprise data warehouse, data marts, and data governance programs, as well as closed loop processing and the integration of structured and unstructured data.

Eckerson finished the article with the statement: "The message is clear: if you want to deliver value to your organization and assure yourself a long-term, fulfilling career at your company, then don’t be satisfied with being just a data provider. Make sure you evolve into a solutions provider that is viewed as a strategic partner to the business."

I agree with him, the BI team as a data provider can meet organizations, but the role of BI team as solution provider allows a more strategic role for BI and facilitates the delivery of value to business.

The Competitive Market of Data Warehousing

Doug Henschen commented about the competitive market of Data Warehousing, in an article published in the Intelligent Enterprise, entitled Upstart Vendors Keep Data Warehousing Competitive, with several announcements from data warehousing upstart vendors at The Data Warehousing Institute (TDWI) World Conference, happened this week in Las Vegas.

He wrote that taken individually, the headlines aren't earth shattering, but taken together, the announcements underscore that the data warehousing universe is expanding, with alternative providers getting stronger despite the pressures of a weak global economy. The announcements are:

- Aster Data: Aster Data nCluster 4.5, an upgrade of its core product featuring a combined SQL/MapReduce visual development environment, a suite of prebuilt analytics modules, support for Fusion-io flash-memory drives, and a new management console for optimizing query performance.

- ParAccel: support for solid state drives (SSDs) from Fusion-io (a move also announced today by Aster Data). SSDs replace spinning, mechanical disks with flash memory chips for faster performance. ParAccel is promising 15 times faster query performance with optional flash SSDs installed by the hardware supplier of the customer's choice.

- Kognitio: GroupM, a division of advertising giant WPP, has asked it to build an analytical environment to match and monitor advertising placements on global scale. GroupM operates in more than 80 countries, and data from these local operations will ultimately be fed into a centralized Kognitio database that will reportedly analyze almost one-third of the world's advertising spend across multiple media outlets.

- Vertica: upgrades including better workload and resource management features aimed at handling mixed query workloads and many more users.

Henschen commented that the data warehousing industry leaders have already embraced flash technology. Oracle put a huge emphasis on flash memory in the Sun-Oracle V2 upgrade of Exadata announced last October. Teradata's SSD-based Extreme Performance Server 4555 was also announced last October, and it's slated for general availability in the first half of this year. IBM has demonstrated an SSD-based test appliance, but it has yet to announce or ship a production SSD-enabled data warehouse appliance. Netezza has used the combination of competitive pricing and fast query performance to win more than 300 customers to date.

Despite the vendor consolidation in several IT categories, the data warehousing market is very competitive, and it is very good, mainly for the customers, that can choose the product that best suits you, to meet their ever increasing needs of data analysis.

Collaborative Data Integration

What Works is a publication with an interesting content, provided by The Data Warehousing Institute(TDWI). In the Volume 27 - August 2009, Philip Russom, Senior Manager of TDWI Research, published a good article entitled Collaborative Data Integration.

He started the article with the definition of TDWI Research for collaborative data integration: A collection of user best practices, software tool functions, and cross-functional project workflows that foster collaboration among the growing number of technical and business people involved in data integration projects and initiatives.

According the article, several trends are driving up the requirements for collaboration in data integration projects:
- Data integration specialists are growing in number
- Data integration specialists are expanding their work beyond data warehousing
- Data integration work is increasingly dispersed geographically
- Data integration is now better coordinated with other data management disciplines
- More business people are getting their hands on data integration
- Data governance and other forms of oversight touch data integration

Different organizational units provide a structure in which data integration can be collaborative:
- Technology-focused organizational structures
- Business-driven organizational structures
- Hybrid structures

"Corporations and other user organizations have hired more inhouse data integration specialists in response to an increase in the amount of data warehousing work and operational data integration work outside of warehousing", he wrote.

"Although much of the collaboration around data integration consists of verbal communication, software tools for data integration include functions that automate some aspects of collaboration", he also wrote. Some features have existed in other application development tools, but were only recently added to data integration tools,like: Check out and check in, Versioning, and source code management features.

About Data Integration Tool Requirements for Business Collaboration: "a few data integration and data quality tools today support areas within the tools for data stewards or business personnel to use. In such an area, the user may actively do some hands-on work, like select data structures that need quality or integration attention, design a rudimentary data flow (which a technical worker will flesh out later), or annotate development artifacts (e.g., with descriptions of what the data represents to the business)".

He explained that collaboration via a tool depends on a central repository: The views just described are enabled by a repository that accompanies the data integration tool. Depending on the tool brand, the repository may be a dedicated metadata or source code repository that has been extended to manage much more than metadata and development artifacts, or it may be a general database management system.

He finished with some recommendations:

- Recognize that data integration has collaborative requirements. The greater the number of data integration specialists and people who work closely with them, the greater the need is for collaboration around data integration.

- Determine an appropriate scope for collaboration. At the low end, bug fixes don’t merit much collaboration; at the top end, business transformation events require the most.

- Support collaboration with organizational structures. These can be technology focused (like data management groups), business driven (data stewardship and governance), or a hybrid of the two (BI teams and competency centers).

- Select data integration tools that support broad collaboration. For technical implementers, this means data integration tools with source code management features (especially for versioning). For business collaboration, it means an area within a data integration tool where the user can select data structures and design rudimentary process flows for data integration.

- Demand a central repository. Both technical and business team members—and their management—benefit from an easily accessed, server-based repository through which everyone can share their thoughts and documents, as well as view project information and semantic data relevant to data integration.

Business Intelligence Usability

The Data Warehousing Institute (TDWI) published a Technology Poster entitled Business Intelligence Usability, designed by Wayne Eckerson, director of TDWI Research at The Data Warehousing Institute.

According TDWI: "Systems theory provides a "limits to growth" archetype that we can apply to BI. It consists of two adjacent feedback loops: one that inhibits growth (a negative reinforcing cycle) and another that accelerates it (a positive reinforcing cycle). Both hinge on a condition called "business outcomes" that represents the BI solution's value to the organization.

In the world of BI, each element within the feedback loops (usability, reputation, spreadmarts, sponsorship, funding, and projects) is a leverage point that BI teams can use to alter the cycle of growth or decline. Usability is perhaps the most critical and the most challenging.

TDWI's BI Usability poster details the four main components and subcomponents that affect usability. BI teams should apply these components and practices to ensure their BI initiative remains in a positive reinforcing cycle."


The four main components and subcomponents that affect usability are:
- Analysis/Design (Roles, Requirements, BI Frameworks)
- Architecture (Data, Performance, Flexibility, Delivery)
- Change Management (Management Expectations, Marketing, Leadership)
- Support (Feedback, Training, Services, Rapid Development)

You can request a free print copy (US and Canada Only) or download a PDF version, in the TDWI website.

The following companies are sponsors of this technology poster: Bi3 Solutions, Incisive Analytics, MicroStrategy and Talend.

BI: The Year in Review

The Data Warehousing Institute (TDWI) published recently, a retrospective called BI: The Year in Review, written by Stephen Swoyer, where he talks about what important happened in BI scenario, in his opinion.

I highlight in the article:

The DW appliance segment gained newfound legitimacy this year, too, thanks to interest from established powers, including Sybase Inc., Teradata Inc., and Oracle Corp., all of which launched dedicated DW systems.

This year might well be remembered as the year in which established DW and BI powers, DW appliance players, and analytics vendors maneuvered to address analytic issues of a new and almost staggering scale. Indeed, a growing desire to use analytic technology against ever-greater volumes of data, by ever-growing numbers of users, helped fuel much of the activity in the DW appliance segment, the traditional DW space, and the BI tools arena.

It was a year of surprising events, including acquisition activity (Microsoft buying DATAllegro), new product entries from non-traditional players (e.g., Sybase and Teradata), and partnerships between appliance vendors and BI players (e.g., Sybase and MicroStrategy; Dataupia and Tableau Software).

In September, Oracle announced its own DW appliance-like deliverable, the Oracle Database Machine, a combined hardware and software solution, sold by Oracle, serviced by Hewlett-Packard Co. (HP). The Oracle Database Machine is powered by a grid of Oracle database servers that distribute queries to Oracle’s HP-powered Exadata storage systems.

A more general response to the problem of making analytic technology more scalable and pervasive can be seen in the rise of specialty DW systems. In this respect, the irruption of upstart DW players, the ambitious expansion of Microsoft’s and Oracle’s DW efforts, and even Teradata’s long-awaited entry into the DW appliance segment are all responses to the same problem. 2008 was just the year in which this long-simmering need finally boiled over.

I think the BI scenario is shifting radically, with new concepts, tools and approaches. 2008 was a year with a lot of news about BI.

The Value of BI in a Weak Economy

Today, Michael Corcoran published a very nice article in The Data Warehousing Institute (TDWI) called The Value of BI in a Weak Economy, where he talks due the financial situation, the CIOs must control spending and many of them are turning to business intelligence (BI) to derive maximum value from their existing assets. He offers several examples that demonstrate why BI is so valuable in a weak economy.

He divides the article by topics, and I would like to highlight some parts of the article:

Using Employee Metrics to Motivate Performance

One way to motivate positive performance is to make employees aware of how they compare to their peers. This information helps these workers make better decisions, and encourages them to work harder to improve their standing in the organization.

SwiftTrade, a financial services firm operating in the North American, European, and Asian markets, reveals how BI holds the key to productivity in lean times. Benson Chung, a member of SwiftTrade’s business process management team, created a BI system that automatically updates a reporting database whenever designated revenue and trading milestones are reached. Additionally, using BI technology, he has created several dynamic reports to motivate trader performance.

Using BI to Identify Cost-Saving Opportunities

One of the ways BI reduces costs is by shortening the time it takes people to get information. At the Hillman Group in Cincinnati, Ohio, a BI application is shrinking that process from weeks to minutes. Nearly 600 sales representatives use BI software to track sales transactions and see if they’re meeting quotas.

Helping a Dealer Network Reduce Costs

Few markets are experiencing economic doldrums like the U.S. automotive industry. As the industry expands to include new Chinese exporters, along with established players from Japan, Germany, and South Korea, one U.S. auto manufacturer used BI technology to create a dealer reporting system that saves $60 million each year. The system identifies excessive repair costs by monitoring how much each dealer’s warranty performance varies from the average performance of other dealers in the same geographic region.

Using BI as a Profit Center

BI can also uncover previously untapped revenue. The genesis of these initiatives is often a desire to fully analyze data about customers, products, and sales. Data visualization software can help

Consider the Commercial branch of Air Canada, which is chartered with understanding how revenue is generated for Canada’s largest commercial airline. To do its job more effectively, managers created an Advance Booking Report (ABR) that calculates revenue and yield for each of the airline’s major markets, sorted by week and month.

Air Canada used this report to answers questions such as the following: Do declines in bookings indicate a trend (such as a mitigating issue with one of the international markets)? Do we have excess capacity, or are the flights likely to be overbooked? Should our sales force investigate a bookings problem?

Air Canada’s data visualization software uses geographic displays to reveal point-of-sale data on a world map. Multiple views are just a click away simply by highlighting a specific data element. Linking interactive graphs makes it easier to detect correlations in the data. For example, they can select a time period and display a scatter plot of routes clustered according to profitability (low bookings with low fares). One more click produces a report that instantly identifies the issue in a single page. This leads to more productive meetings, better understanding of the issues, and more clearly defined follow-up activities.

Positioned for Growth

Many business leaders are looking to BI for near-term solutions, but BI delivers high-value returns on many levels. BI enables companies to work smarter, even when tight financial times mean smaller IT budgets and leaner staffs. Market-leading companies in every industry are turning to this software to stay ahead. When the economy turns—as it inevitably will—these are the firms that will be in the best position to seize the next wave of opportunities.

It is a very nice article, and I also believe that with the weak economy and recession around the world, to use BI is the right way to help companies to make decisions smarter and faster.

The Power of Dynamic BI

TDWI published last week, a Q&A with Cliff Longman, CTO of Kalido, by James E. Powell, called The Power of Dynamic BI.

Cliff Longman did several interesting comments:

- Dynamic BI is business intelligence that is adaptable enough that it can deliver answers to business questions in time for those answers to be useful.

- How dynamic your BI needs to be depends on the business questions asked of it. Some questions might need answers within an hour, others within a month. Your current BI infrastructure may be able to answer some questions while others will push the infrastructure to a breaking point.

- Dynamic BI goes beyond traditional BI, delivering answers not only to the questions the business asked when the BI system was first installed, but also to new questions that come up daily: How does our company look post-merger? What would happen if we changed our sales territories? Is my current marketing promotion having an impact on sales?

- Many or most traditional BI implementations have difficulty delivering dynamic BI, since every change requires some reconfiguration of the data structure behind the BI tool. Often, by the time the system is ready to provide answers, it's irrelevant -- the opportunity has passed or decisions have already been made.

- It's often difficult for IT and business managers to ensure that the BI infrastructure truly reflects the business model. That's partly because business managers can't easily understand a data model, and therefore can't validate it or suggest changes. As a result, data warehouses are often built in ways that do not reflect the business.

- Even when the data structure reflects the business, the data warehouse infrastructure supporting this structure is rigid and difficult to change.

- Business modeling tools capture the way a business works in a medium that can easily be understood by both business managers and IT. With translation barriers eliminated, BI projects are more likely to address the needs of business managers out of the gate, and can easily be modified to address future changes.

- If the data structure is actually based upon and driven by the business model, then changes to the business model can be automatically reflected in the data structure. This limits the issues that come with changing a data warehouse's schema, and speeds the delivery of BI system answers to new business questions. This approach makes business intelligence far more dynamic.

Comments about TDWI World Conference

TDWI World Conference happened last month, provided by The Data Warehousing Institute (TDWI), and here are some links with posts and articles commenting on the conference:

- TDWI in San Diego - the New and the Niche - Cindi Howson - BIScorecard
- Open Source Blossoms at TDWI - Mark Madsen - Intelligent Enterprise
- Cross the BI-Web Analytics Divide - Tony Byrne - Intelligent Enterprise
- The Velocity of eBay - Jim Ericson - DM Review
- How to make networking fun - Ericka Wilcher - The Sascom Magazine Blog
- Better than free food at TDWI San Diego - Ted Cuzzillo - Datadoodle
- Makin' Friends at TDWI San Diego - Jill Dyche - B-Eye-Network

TDWI's Technology Poster about Master Data Management

The Data Warehousing Institute (TDWI) published Technology Poster about Master Data Management, designed by Philip Russom, senior manager of TDWI Research. According TDWI: the Master Data Management poster sorts out the complex layers of the MDM stack, illustrating how people, practices, and software automation are coordinated in a mature MDM implementation.

This poster will help explain:
- The tools, technologies, and techniques that go into the MDM technology stack.
- How the tech stack adjusts to practices like operational MDM and analytic MDM.
- How the MDM technology stack is influenced by pre-existing systems, architectural approaches, growth over time, and build-versus-buy decisions.

This kind of poster is very interesting, because it can be used to explain how MDM works in two ways, first as an overview and after detailing each layer of the process.


Philip Russom tells what he imagined to create the poster:
"On a break during the TDWI World Conference in Chicago this May, I left the hotel and walked up the street to the Museum of Contemporary Art. As soon as I entered, I saw mobiles by the great American sculptor Alexander Calder. My head was spinning from the technical presentations I’d seen at the conference, and it struck me that Calder mobiles resemble the way we draw technology stacks and system architectures. Both are compartmentalized, yet the parts are connected and interactive. Both move and evolve slowly as the winds of change brush them.

Later, when I needed a metaphor for the many pieces that master data management connects and coordinates, I naturally thought of Calder’s elegant and organic mobiles.

As you look at the poster, try to imagine the pieces in motion like a Calder mobile, with the operational, analytic, and enterprise practices spinning, and the balance shifting from collaboration to implementation and back again.

My thanks to Deirdre Hoffman for translating my ideas into the graphic images of this poster."

You can request a free print copy (US and Canada Only) or download a PDF version, in the TDWI website (registration required).

The following companies are sponsors of this technology poster: Baseline Consulting, BizGui Inc, EasyAsk, Exeros, MicroStrategy, Syncsort, Talend.

TDWI World Conference

The Data Warehousing Institute (TDWI) will promoting their TDWI World Conference, from 17 until 22 August, in San Diego, California.

This is a great opportunity to attend courses, lectures and presentations with the main speakers of DW/BI/PM fields, and also to visit the stands where the leading providers of hardware, software, and services for business intelligence, data warehousing, and related technologies will demonstrating their solutions.

The courses are divided by subjects: Leadership & Management, Business Analytics, Administration & Technology, Data Analysis & Design, Data Integration, Career.

The Keynote Presentations are:
- Howard Dresner - Information Democracy—Information Equality for All!
- Bill Schmarzo- BI Meets Web Analytics: Through the Looking Glass


Co-located with TDWI’s World Conference, will happen the TDWI BI Executive Summit, from 18 until 20 August, with Special Focus on Analytics. The TDWI explains the difference between the two events and also explains that the BI Summit is important to the participants to validate their understanding of best practices, and stay on top of the latest research, trends, and technologies in the industry.

Four Steps to Effective Performance Management

Leah MacMillan, vice president of product marketing at Cognos, published a nice article on TDWI, a couple of weeks ago, called Four Steps to Effective Performance Management. In the article, she describes the four-step process that organizations should to follow to define an effective PM.

The four steps are:
- Addressing Initial Needs
- Driving Insight through BI
- Extending BI Across the Enterprise
- Advancing Your Business through PM

She finishes the article commenting what she thinks be the main benefits when you are following the roadmap proposed.

In my opinion, all the process pass through an essential issue, the alignment between the IT and the business, that I consider nowadays one of the most important steps to an effective Performance Management.

Articles about Master Data Management

Recently, I have read several interesting articles related with the importance of Master Data Management for the companies. Some of them are:


Last week, the DM Review published, in its online edition, an article entitled The Intrinsic Value of Master Data Management, by Lyndsay Wise. In the article, she wrote the benefits to IT and business to build a MDM solution in a corporation.


Last month, Scott Lee wrote in online edition of BI Review, the experience in implementing MDM in the company where he works. In the article, called Master Data Management is a Program; he explains the adopted strategy, considering the MDM doesn't a single project, but a continuous program.


TDWI published last month, an article by Todd Goldman: Best Practices in MDM: Cross-System Data Analysis, where he wrote about Cross-system source-data discovery and data mapping, that he thinks being importants steps to a well implementation of MDM.

TDWI Best Practices Awards

Today, April 21, is the deadline to apply to TDWI Best Practices Awards, a contest organized by TDWI (The Data Warehousing Institute).

According TDWI, this contest is "designed to identify and honor companies that have demonstrated best practices in developing, deploying, and maintaining applications for business intelligence, data warehousing, and related data management areas (like data quality and master data)".

I think it is a good incentive to companies that have a well implemented BI/DW application.