It seems that juggling is the most useful of all skills when embarking on a data warehousing project. During the discovery and analysis phase, the workload grows insanely large, like some mutant science fiction monster. Pressures to deliver can encourage rampant corner-cutting to move quickly, while the need to provide value urges caution in order not to throw out the proverbial baby with the bath water as the project speeds along. Change data capture is one area that is a glaring example of the necessary juggling and balancing.

Datawatch Corporation, provider of information optimization solutions, has announced a strategic partnership with Lavastorm Analytics, an analytics software vendor, to provide customers the ability to expand their use of unstructured and semi-structured data sources when developing analytic applications.

Dimensions are the workhorses of a multidimensional design. They are used to manage the numeric content being analyzed. It is through the use of dimensions that the metrics can be sliced, diced, drilled-down, filtered and sorted. Many people relate to dimensions by thinking of them as reference tables. Such thoughts aren't exactly accurate. A dimension groups together the textual/descriptor columns within a rationalized business category. Therefore, much of the content coming from relational tables may be sourced from reference tables, but the relationship between each source reference table and the targeted dimension is unlikely to be one-for-one. These grouped-format dimensions often contain one or more hierarchies of related data items used within the OLAP queries supported by the structures.

Do not allow well-meaning but confused proponents to obscure concepts related to normalization and dimensional design. Under a normalized approach one usually would not expect for numeric data items and textual data items to fall into different logical relations when connected to the same entity object. Yet within a multidimensional approach that is exactly what happens. Multidimensional design and normal design are not the same, and one should not expect to claim that both approaches were used and that they resulted in the same data model.

Establishing a data warehousing or business intelligence environment initiates a process that works its way through the operational applications and data sources across an enterprise. This process focuses not only on identifying the important data elements the business lives and breathes, but the process also tries very hard to provide rationality in explaining these elements to business intelligence users.

Sonata Software, an IT consulting and software services provider headquartered in Bangalore, India, has announced its center of excellence (CoE) for Exalytics, Oracle's engineered system designed for high performance data analysis, modeling and planning.

Establishing a data warehousing or business intelligence environment initiates a process that works its way through the operational applications and data sources across an enterprise. This process focuses not only on identifying the important data elements the business lives and breathes, but the process also tries very hard to provide rationality in explaining these elements to business intelligence users.

Establishing a data warehousing or business intelligence environment initiates a process that works its way through the operational applications and data sources across an enterprise. This process focuses not only on identifying the important data elements the business lives and breathes, but the process also tries very hard to provide rationality in explaining these elements to business intelligence users.

Multi-dimensional design involves dividing the world into dimensions and facts. However, like many aspects of language, the term "fact" is used in multiple ways. Initially, the term referred to the table structure housing the numeric values for the metrics to be analyzed. But "fact" also is used to refer to the metric values themselves. Therefore, when the unique circumstances arise wherein a fact table is defined that does not contain specific numeric measures, such a structure is referred to by the superficially oxymoronic characterization of a "factless fact."

Multi-dimensional design involves dividing the world into dimensions and facts. However, like many aspects of language, the term "fact" is used in multiple ways. Initially, the term referred to the table structure housing the numeric values for the metrics to be analyzed. But "fact" also is used to refer to the metric values themselves. Therefore, when the unique circumstances arise wherein a fact table is defined that does not contain specific numeric measures, such a structure is referred to by the superficially oxymoronic characterization of a "factless fact."

Multi-dimensional design involves dividing the world into dimensions and facts. However, like many aspects of language, the term "fact" is used in multiple ways. Initially, the term referred to the table structure housing the numeric values for the metrics to be analyzed. But "fact" also is used to refer to the metric values themselves. Therefore, when the unique circumstances arise wherein a fact table is defined that does not contain specific numeric measures, such a structure is referred to by the superficially oxymoronic characterization of a "factless fact."

Within the information technology sector, the term architect gets thrown around quite a lot. There are software architects, infrastructure architects, application architects, business intelligence architects, data architects, information architects, and more. It seems as if any area may include someone with an "architect"status. Certainly when laying out plans for a physical building, an architect has a specific meaning and role. But within IT "architect" is used in a much fuzzier manner.

Micro Focus, a provider of enterprise application modernization solutions, announced it is shipping a new release of its COBOL application migration toolset, with support for Microsoft's latest operating system and integrated development environment. Visual COBOL 2.1 also includes many enhancements designed to facilitate an improved application developer experience, as well as deliver an upgrade path for core business applications. "With support for the Windows 8 platform, Visual COBOL provides even greater developer productivity, collaboration, and quality improvements while reducing their costs and time to market," Ed Airey, Micro Focus product marketing director for COBOL Products, tells 5 Minute Briefing.

Within the information technology sector, the term architect gets thrown around quite a lot. There are software architects, infrastructure architects, application architects, business intelligence architects, data architects, information architects, and more. It seems as if any area may include someone with an "architect"status. Certainly when laying out plans for a physical building, an architect has a specific meaning and role. But within IT "architect" is used in a much fuzzier manner.

A new educational webcast examines the results of the 2012 IOUG Test, Development & QA Survey, and covers the best practices and issues that it highlights. Mining the data assets being gathered from all corners of their enterprise, including transactions, customer data, employee input, and information about market conditions, has been essential to companies in uncovering new opportunities, but, in the rush to deliver results, many IT and development departments take shortcuts within the testing process, taking live data right out of production environments to run through testing, development and quality assurance processes.

In writing a definition for an entity, an attribute, or any other element within a database design, the desired end is a descriptive text that is clear, factual and concise. Semantics are an ambiguous and often painful tool to employ. Balancing the need for clarity against the desire to avoid redundancy can be a juggling act that is hard to accomplish. One might not easily recognize what is complete versus what is lacking, versus what has gone too far. But even so, within a definition if one finds oneself listing valid values and decoding the value's meaning, then one has likely already moved beyond what is "concise." Lists of values easily add bulk and quantity of verbiage into a definition, yet such lists do not usually increase the quality of a definition.

The beauty of a truly wonderful database design is its ability to serve many masters. And good database designers are able to empathize with those who will use their designs. In business intelligence settings, three perspectives deserve consideration when composing designs.

Software operates the products and services that we use and rely on in our daily lives. It is often the competitive differentiation for the business. As software increases in size, complexity, and importance to the business, so do the business demands on development teams. Developers are increasingly accountable to deliver more innovation, under shorter development cycles, without negatively impacting quality. Compounding this complexity is today's norm of geographically distributed teams and code coming in from third-party teams. With so many moving parts, it's difficult for management to get visibility across their internal and external supply chain. Yet, without early warning into potential quality risks that could impact release schedules or create long term technical debt, there may be little time to actually do something about it before the business or customers are impacted.

CA Technologies has announced a major new release of the ERwin data modeling solution. This new release which is the second in less than a year provides a collaborative data modeling environment to manage enterprise data using an intuitive, graphical interface. It helps improve data re-use, optimize system quality, accelerate time-to-benefit and enable appropriate information governance—key objectives for IT organizations serving companies in today's highly competitive and closely regulated markets.

It is an understatement to say we're witnessing an example of Moore's Law — which states the number of transistors on a chip will double approximately every two years — as we seek to manage the explosion of big data. Given the impact this new wealth of information has on hundreds of millions of business transactions, there's an urgent need to look beyond traditional insight-generation tools and techniques. It's critical we develop new tools and skills to extract the insights that organizations seek through predictive analytics.

It is an understatement to say we're witnessing an example of Moore's Law — which states the number of transistors on a chip will double approximately every two years — as we seek to manage the explosion of big data. Given the impact this new wealth of information has on hundreds of millions of business transactions, there's an urgent need to look beyond traditional insight-generation tools and techniques. It's critical we develop new tools and skills to extract the insights that organizations seek through predictive analytics.

The beauty of a truly wonderful database design is its ability to serve many masters. And good database designers are able to empathize with those who will use their designs. In business intelligence settings, three perspectives deserve consideration when composing designs.

An educational and interactive webcast will review the findings of the 2012 IOUG Test, Development and QA Survey and discuss the best practices and issues that it highlights. This IOUG study was conducted by Unisphere Research, a division of Information Today, Inc., and sponsored by IBM. Presented by Kimberly Madia, WW product marketing manager at IBM, and Thomas Wilson, president and CEO, Unisphere Research, the webcast will be held Thursday, September 27, from 12 - 1 PM CDT. Attendees to the webcast will receive a copy of the study report.

It seems easy to fall into a state where projects and activities assume such soft-focus that routine takes control, where one simply does necessary tasks automatically, no questions are raised regarding what is moving through the work-life production line and everyone is essentially asleep at the switch. Certainly, we may have one eye open ensuring that within a broad set of parameters all is well, but as long as events are basically coloring inside the borders we continue allowing things to just move along. In this semi-somnambulant state we can easily add columns to tables, or even add new entities and tables, or triggers and procedures to our databases, then eventually at some point down the road have someone turn to us and ask, "Why this?" or, "What does this really mean?" And at that point, we surprise ourselves with the discovery that the only answer we have is that someone else told us it was what we needed, but we do not really understand why it was needed.

An educational and interactive webcast will review the findings of the 2012 IOUG Test, Development and QA Survey and discuss the best practices and issues that it highlights. This IOUG study was conducted by Unisphere Research, a division of Information Today, Inc., and sponsored by IBM. Presented by Kimberly Madia, WW product marketing manager at IBM, and Thomas Wilson, president and CEO, Unisphere Research, the webcast will be held Thursday, September 27, from 12 - 1 PM CDT. Attendees to the webcast will receive a copy of the study report.

The whole world can be divided into two groups, these being splitters and lumpers. Design battles are waged across conference rooms as debates rage over whether to split or to lump. Splitters take a group of items divide them up into sub-groups and sub-sub-groups occasionally going so far as to end with each lowest level becoming a group of one. On the other side of the design fence, lumpers combine items until everything is abstracted into group objects covering very broad territory, such as a "Party" construct, or ultimately an "Object" object. Within data modeling, arguments arise, such as whether to sub-type an entity. Or perhaps lumping is discussed as the grain of a multidimensional fact is proposed. This debate underlies much of the decision-making involved in determining what domains to create within a data model. The split-versus-lump issue is ubiquitous and universal. The question to split or lump arises across many kinds of choices, in addition to the entity definition, table grain, or the domain grain mentioned in the previous examples; this issue is at the heart of deliberations regarding establishing functions, overriding methods, or composing an organizational structure.

SAP has announced that the PowerBuilder Developers Conference will be held October 15-19, 2012, at the Venetian Resort Hotel in Las Vegas, concurrently with SAP TechEd Las Vegas 2012. The conference will be comprised of an opening keynote at SAP TechEd, followed by a PowerBuilder general session and PowerBuilder technical breakout sessions.

In the dim, dark past of data warehousing, there was a time when the argument was put forward that "history does not change." It was posited that once a piece of data was received by the data warehouse, it was sacrosanct and nonvolatile. A fact record, once processed, was to remain unchanged forever. Dimensions, due to their descriptive nature, could be changed following the prescribed Type 1, 2, or 3 update strategies, but that was all. It was the expectation that due to their very nature, fact tables would become huge and in being huge would give poor update performance; performance so poor that updates would be virtually impossible to enact.

It seems only reasonable that what one person can do, others can learn. On the other hand, taking people through training does not usually result in the creation of great new database administrators (DBAs). It often appears as if those who are exceptional at the craft operate at higher levels as they dive into a problem. Can training alone provide folks with the attention to detail, the urge to keep digging, or the ability to recall minutiae that allow them to rise from simply holding the DBA title to becoming someone who is a great DBA? Or must the genetic potential exist first, and then one might fall into the DBA occupation and astound those around them. It is very hard to say with any degree of certainty whether great DBAs are made or born; yet again the battle between nature and nurture arises.