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Microsoft Unveils Database Products at PASS Conference  

Microsoft released the first community technology preview (CTP) for the next-generation version of SQL Server, codenamed Denali, Nov. 9. But that is just one of several announcements to come out of the PASS Summit 2010 conference in Seattle this week. In addition to unveiling Denali, Microsoft also announced the release of SQL Server 2008 R2 Parallel Data Warehouse and the new Critical Advantage Program, which offers an end-to-end suite of pretested hardware and software configurations, services and support.

“SQL Server code-named Denali will help empower organizations to be more agile in today’s competitive market,” the SQL Server Team touted on its blog. “Customers will be able to efficiently deliver mission-critical solutions through a highly scalable and available platform. Industry-leading tools will help developers quickly build innovative applications while data integration and management tools help deliver credible data reliably to the right users and new user experiences expand the reach of BI to enable meaningful insights.”

More on EWeek

101 Ways to Sabotage Your Predictive Analytics Project  

And there is the first five here. Interesting Read, I liked it.

The strategic approach and project design for predictive analytics is substantially different than the other areas of business intelligence. Unlike a data warehouse design, which is similar to an engineering project, predictive analytics and data mining are a discovery process. And while several consortiums have standardized formal processes to accommodate discovery and iterative process, the practice remains riddled with common pitfalls.

Those who make the effort to educate themselves on the industry-standard approach to predictive analytics are nearly assured to reap residual returns – long before their counterparts who typically rush to acquire a tool and dive headlong into the data.

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Written by Guru Kirthigavasan

May 18th, 2010 at 6:22 pm

Rising Tide in the Data Warehouse vs. Data Mart Debate  

Is building an enterprise data warehouse (EDW) the best path to business intelligence (BI)? It’s a perennially vexing question that — thanks to a couple of recent trends in BI and data warehousing (DW) — has taken on new life.

The value of the full-fledged EDW seems unassailable. Over the last half-decade, however, some of the biggest EDW champions have moderated their stances, such that they now both countenance the existence of alternatives and, under certain very special conditions, are even willing to admit they’re useful. The result is that although the EDW is still seen as the Holy Grail of data warehousing, departmental (and even enterprise) data marts are now countenanced as well.

Active EDW giant Teradata Inc. is the foremost case in point, but other players — including relative newcomer Hewlett-Packard Co. (HP), which is in the high-end DW segment (by its acquisition of Knightsbridge Solutions) and markets Neoview, a DW appliance-like offering — are staking out similar ground. (In addition to Neoview, HP also partners with both Microsoft Corp. and Oracle Corp. to market appliances in the 1 to 32 TB range.)

Interesting debate on TDWI.

The Elusive Virtual Data Warehouse  

Bill Inmon writes on the virtual data warehouse. Interesting Read.

Why then is the virtual data warehouse such a supremely bad idea? There are actually lots of reasons for the vacuity of virtue manifested by the virtual data warehouse. Some of those reasons are:

A query that has to access a lot of databases simultaneously uses a lot of system resources. In the best of circumstances, query performance is a real problem.

A query that has to access a lot of databases simultaneously requires resources every time it is executed. If the query is run many times at all, the system overhead is very steep.

A query that has to access a lot of databases simultaneously is stopped dead in its tracks when it runs across a database that is down or otherwise unavailable.

A query that has to access a lot of databases simultaneously shuffles a lot of data around the system that otherwise would not need to be moved. The impact on the network can become very burdensome.

A query that has to access a lot of databases simultaneously is limited to the data found in the databases. If there is only a limited amount of historical data in the databases, the query is limited to whatever historical data is found there. For a variety of reasons, many application databases do not have much historical data to begin with.

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Written by Guru Kirthigavasan

March 22nd, 2009 at 7:17 am

High-Performance dB and DWH Solution from Greenplum and Sun  

From the Press Release -

Greenplum, a leading provider of database software for business intelligence, and Sun Microsystems, Inc. (NASDAQ: JAVA) today announced that Reliance Communications is using Greenplum Database, running on the Sun Data Warehouse Appliance, to power a range of applications, from legal and regulatory compliance to call detail record analysis.

Greenplum Database is the world’s fastest, most cost-effective solution for analyzing the massive amounts of information generated by surging worldwide usage of wireless and broadband services. The Data Warehouse Appliance powered by Sun and Greenplum is the industry’s first cost-effective, high-performance super-capacity data warehouse appliance. Purpose-built for high-performance, large-scale data warehousing, the solution integrates best-in-class database, server, and storage components into one easy-to-use, plug-and-play system.

“The Sun Data Warehouse Appliance running Greenplum Database is helping Reliance meet its goal of superior responsiveness in a challenging data environment — one that is characterized by rapid growth and increasing user demand,” said Raj Joshi, VP and Head (Decision Support Systems) at Reliance Communications Limited. “Deploying the joint Greenplum and Sun solution improved our response times and enabled Reliance Communications to improve our data management.”

Reliance Communications Limited is the telecommunications company of Reliance ADA Group which is one of India’s largest industrial groups. Reliance Communications is known for its innovative market offerings and practices. As Reliance has grown to more than 40 million subscribers, providing accurate and timely data support and analytics to all parts of the business has been a challenge. Turning an ad hoc request from historical records could take multiple hours; even loading a day’s worth of data into the system could take up to three hours.

Sybase and Sun create the World’s Largest Data Warehouse  

One Petabyte of mixed relational and unstructure data. That’s neat.

More from the Sybase Press Release -

Sybase, Inc. (NYSE: SY), the largest enterprise software and services company exclusively focused on managing and mobilizing information, today announced that the Sybase® IQ analytics server has set a new Guinness World Record™ by powering the world’s largest data warehouse on a Sun™ SPARC® Enterprise M9000 server. This accomplishment was achieved using Sybase IQ, BMMsoft ServerSM and the Sun Microsystems® Data Warehouse Reference Architecture. This winning combination enables more data to be stored in less space, searched and analyzed in less time, while consuming 91 percent less energy and generating less heat and carbon dioxide than conventional solutions.

Powered by the category-leading column-oriented database Sybase IQ, the data warehouse is certified to support a record-breaking one petabyte of mixed relational and unstructured data—more than 34 times larger than the largest industry standard benchmark1 and twice the size of the largest commercial data warehouse known to date2. In total, the data warehouse contains six trillion rows of transactional data and more than 185 million content-searchable documents, such as emails, reports, spreadsheets and other multimedia objects.
Designed from the ground up as an analytics server, Sybase IQ produces its impressive results because of a unique architecture combining a column-oriented data structure with patented indexing and a scalable grid. Sybase IQ offers extraordinarily high performance at a lower cost than a traditional, row-oriented database. And, unlike traditional row-based data warehouses, the stored data in Sybase IQ is compressed by up to 70 percent of its input size, creating the most optimal and elegant analytics solutions.

“The results of this benchmark showcase Sybase IQ’s capabilities to handle real-world scenarios, querying vast amounts of data representing the transactions processed across the worldwide financial trading networks over multiple years.” said Francois Raab, president, InfoSizing, the consulting firm that oversaw the benchmarking of the record. “Sybase IQ has proven its production strength in handling the volume of multimedia documents representative of the electronic communication between half a million financial traders.”

Teradata Announces New Family of Analytical Platforms  

Teradata Corporation has introduced a new family of platforms from entry-level to active enterprise data warehouses that addresses many customer needs (especially of Indian and other similar markets). Powered by the Teradata 12.0 database engine, the family includes Teradata 550 SMP (symmetric multiprocessing), Teradata 2500, and Teradata 5550.

Teradata 550 SMP is a departmental data warehouse, designed to meet customers’ need for a smaller, less expensive system. It is simple to set up and can use the Novell SUSE Linux 64-bit operating system or Windows. In addition, customers can license and run the Teradata 12 database on their choice of Intel-based platforms, starting at $40,000. Teradata Express Edition, a free developer version of Teradata 12, is available to work on Windows servers and laptops for development, testing and learning.

From EFY News article.

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Written by Guru Kirthigavasan

May 15th, 2008 at 6:23 am

Data Warehousing on a Shoestring Budget  

TDWI is running a series on developing and deploying Data Warehousing, frugally. It’s a 3 part series. Read Part 1 and 2.

Although seemingly difficult, you can make choices, which allow for the beneficial realization of data warehousing while also minimizing costs. By balancing technology and carefully positioning your business, your organization can quickly create cost-effective solutions using data warehousing technologies.

There are a few simple rules to help you develop a data warehouse on a shoestring budget:

* Use what you have
* Use what you know
* Use what is free
* Buy only what you have to
* Think small and build in phases
* Use each phase to finance or justify the remainder of the projects

It’s also a must read for businesses which have enough business sponsorship and enormous resources. Tough times in the marketplace like these call for an economical way of staying ahead on the business curve. And that’s exactly the point of this series.

I like the detailed approach Nathan Rawling towards this topic.

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May 13th, 2008 at 9:24 pm

Data Warehousing and Appliance Model ?  

Netezza co-founder Foster Hinshaw, who recently founded a new company Dataupia, talks about the new class of Data Warehouse Appliance.

Unlike existing appliances, Dataupia plugs right into or sights right underneath an organization’s existing RDBMS assets. As far as a DBA or data warehouse architect is concerned, Dataupia claims, it isn’t even there

From the Q & A Session with Foster -

Is that an advantage of the data warehouse appliance model, this ability to — I assume inexpensively, or comparatively inexpensively — host several years of data and make it available for rapid querying by users? Or is that more kind of an evolving status quo — sort of where data warehousing itself is heading?

I think it’s absolutely an advantage [of the data warehouse appliance]. Because of the affordability of our solution, it changes some of the things that you can do with your business and allows you to get more granular details, maybe more toward that one-to-one understanding of your customers. So you can tell historically over the last several holiday seasons what they’ve done for each holiday season, and that enables you to do really what you couldn’t do in the past.

As the users get on to the system, they’re doing types of queries [and] types of analytics they never thought about doing before. That’s what I love. When you see customers trying to do stuff and they say “Wow!”

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Written by Guru Kirthigavasan

February 4th, 2008 at 7:26 am