DB2 Alphablox are Blocks

Our group has been assigned to develop solutions for IBM DB2 Alphablox and We have enjoyed this tool and discovered it's unique advantages.

For business owners/managers and IT decision makers, I understand that Business Intelligence (BI) is almost a requirement nowadays. BI will allow you to make timely and efficient decisions based on appropriate facts.

Alphablox allows you to "INTEGRATE" a BI Solution without modifying your existing IT Infrastructure. The Total Cost of Ownership (TCO) is definitely much cheaper and is highly portable in case any changes is deemed necessary by your company.

DB2 Alphablox and all DB2 Alphablox analytic-enabled solutions run as J2EE-compliant applications in the application server. In the reference figure above, your Alphablox component will sit comfortably inside the J2EE Application Server (Web-Application-Tier).

For more information, you can download the Technical WhitePaper of IBM DB2 Alphablox - click here.

Related Articles:
1. Who is Alphablox before IBM acquired them
2. 10 technical things every DB2 Alphablox Developer should know
3. Blox Team Pics and Why we choose Alphablox

Gilbert on Monday, February 27, 2006 0 Comments

Business Intelligence Links

There are lots of blogs and websites that speaks their actual experiences with different BI Applications, Databases and Data Warehousing Tools. If you want an aggregated view, I suggest visiting BI BLOGS.

Here are a select few blogs from different BI application users in the market today:

1. Steve Nagoski - Business Objects Enterprise BI Platforms.
2. InfoCaptop - Oracle Business Intelligence Discoverer.
3. Marco Russo - SQL Server Analysis Services 2005.
4. Patrick Husting - Office Business Scorecard Manager 2005
5. Ian Tien - Business Scorecard Manager 2005
6. Chris Webb - Microsoft BI

Open Source Solutions for your Business Intelligence, Database, Data Warehousing needs:

Open Source Database
1. Derby - relational DB done entirely in Java.
2. EnterpriseDB - RDBMS, PostgreSQL, compatible with Oracle apps.
3. Firebird - relational DB offering many ANSI SQL standard features.
4. Ingres - OS independent relational DB.
5. MySQL - the most popular open source database.
6. PostgreSQL - enterprise and secure relational database.
7. Sleepycat - a relational DB that has a library with a programatic API. (Acquired by Oracle on Feb 14, 2006)

Open Source ETL
1. Pequel ETL - Comprehensive & high performance data processing/transform system done in Perl/C.
2. Clover ETL - Java based ETL framework which can be used to transform structured data.
3. CpluSQL - distributed ETL tool extracts and transforms row based data from databases and flat files.
4. Enhydra Octopus - Java based ETL framework that connect to JDBC Sources and transforms them to XML file.
5. JetStream - Java Extraction Transformation Service for Transmitting Records & Exchanging Application Metadata: a Java-based ETL/EAI tool.
6. KETL on Bizgres - Kinetic ETL, created by KineticNetworks.
7. KETTLE - LGPL License ETL tool that utilizes XML and generates its own SQL queries.
8. openDigger - java based compiler for the xETL language.

Open Source Reporting Tools
1. Agata Report - cross-platform database reporting tool with graph generation and a query tool that allows you to get data from PostgreSQL, MySQL, SQLite, Oracle, DB2, MS-SQL, Informix, InterBase, Sybase, or Frontbase and export that data as PostScript, plain text, HTML, XML, PDF, or spreadsheet (CSV) formats through its GUI.
2. DataVision - written in Java, very similar to Crystal Reports that uses drag and drop functionality to get data from and data that uses JDBC and export that data as HTML, XML, PDF, LaTeX2e, DocBook, or tab- or comma-delimited text files.
3. Jasper - Java reporting tool that has the ability to deliver rich content onto the screen, to the printer or into PDF, HTML, XLS, CSV and XML files.
4. OpenReports - flexible web based reporting solution that uses JasperReports.
5. OpenRPT - a graphical report writer and rendering engine and the first fully cross-platform SQL report writer.

Open Source BI Suite
1. BEE Project - BI Suite of tools ideal for mid size companies that has 50GB or less of data. It has ETL and uses ROLAP and is under the GPL license.
2. Bizgres - a "distribution" of PostgreSQL with add-on tools, such as JDBC, the JavaLoader, autovacuum and the Configurator, and others for easy BI and DW use.
3. Greenplum - first open source powered database server that can scale to support multi-terabyte data warehousing demands.
4. MarvelIT - open source Business Intelligence solution based on the Apache Jetspeed Enterprise Portal and the popular OpenReports reporting application.
5. OpenI - simple web application that does out-of-box OLAP reporting
6. Pentaho - enterprise-class reporting, analysis, dashboard, data mining and workflow capabilities.
7. SpagoBI - complete suite for the development of Business Intelligence that covers data and metadata organization, static reporting and dimensional analysis, hidden information discovering by means of data mining techniques, the building of a structured and dynamic control suite with dashboard components.
8. Palo - GPL Licensed MOLAP reporting that easily integrates various MS Excel. Ideal if your company is working heavily on Microsoft Excel.

Open Source BI Suite
1. Eclipse BIRT - open source, Eclipse-based reporting system that integrates with your application to produce compelling reports for both web and PDF.
2. EFEU -
3. JpGraph -
4. PostgreSQL MDDB -

Open Source Data Modeling

Gilbert on Wednesday, February 22, 2006 2 Comments

The Blox Team

This blog is maintained by four DB2 Alphablox developer, each taking a focus on the different aspect of the technology.

We love the product and we were group together to develop solutions about IBM DB2 Alphablox for Enterprise.

We are also a strong believer of the Open Source Community and we intend to understand, discover, share and contribute with the endeavors of the community.

Gilbert on Wednesday, February 22, 2006 3 Comments

DB2 Alphablox

DB2 Alphablox in LAYMAN TERMS
DB2 Alphablox is a CUSTOM Business Intelligence (BI) and 100% web-based tool.

If you are a fan of LEGO BLOCKS, you'll understand that you can construct/create 'almost' limitless amount of designs from a certain number of blocks.

With IBM DB2 Alphablox, you can custom made your companies own BI Tool using BLOX much the same way as LEGO does. It's good because you are not automatically tied to a specific technology or brand. It's good also because you and your consultants can ALWAYS find a way to integrate these new tool to your business process.

DB2 Alphablox provides a set of analytic components and supporting services to make it easy to rapidly assemble analytic applications using Java™ Server Pages (JSP) tags. These components, known as "Blox" (as in "building blocks"), are based on the Java 2 Enterprise Edition (J2EE) architecture and are deployed on a Web application server. Visual Blox include highly interactive graphs, charts, and reports. These visual Blox work with data Blox to support analysis of both relational and multidimensional data.

DB2 Alphablox developers use Blox to connect to databases, retrieve information, and tailor the presentation to suit users' needs. Administrators deploy DB2 Alphablox applications into Web application servers, such as IBM's WebSphere® Application Server, BEA's® Weblogic, or the Apache Jakarta Project's Tomcat servlet engine.

Each of the major Blox enables users to interactively explore and analyze data. For example, users can export data to Adobe PDF files or Microsoft® Excel spreadsheets, hide columns in a report, create traffic-light style reports based on specified column values, alter the format of a displayed chart, and so on. The services Blox can be used to provide guided analysis, personalization, customization, and collaboration facilities. Blox users can customize these capabilities and services through JSP tags to provide the right function to a wide range of business users and analysts.

For an example of how DB2 Alphablox work in a real world scenario, you may refer to this articles in IBM DeveloperWorks:
Build Web-based analytic applications with DB2 Alphablox and DB2 Information Integrator


DB2 Alphablox for Unix and Windows adds new capabilities to the IBM business intelligence portfolio, a key foundation for our on demand capabilities.

Optimized for rapid application delivery and deployment, DB2 Alphablox provides a component-based, comprehensive framework for integrating analytics into existing business processes and systems. By implementing solutions that include DB2 Alphablox capabilities, leading enterprises maximize the value of their information assets by delivering business insight to the right people at the point-of-decision.

Leading enterprises in financial services, manufacturing, technology, pharmaceuticals, telecommunications, retail, and energy, are successfully leveraging DB2 Alphablox technology inside a wide variety of integrated analytic solutions. DB2 Alphablox enables organizations to integrate analytics across all functions and lines of business, and enable powerful analytic solutions to business users at the front lines for improved decision making. It enables customers and partners to optimize various aspects of their business solutions, including:
- Self-service reporting and analysis applications
- Operational analysis applications
- Financial reporting and analysis applications
- Planning applications
- Business Performance and Key Performance Indicator (KPI) Dashboards

DB2 Alphablox's open architecture and component approach to application development provide for a high degree of customization when delivering analytic solutions, and offer numerous options for application front-end interfaces to meet the requirements of the casual to the power user.

Related Articles:
1. Who is Alphablox before IBM acquired them
2. 10 technical things every DB2 Alphablox Developer should know
3. Blox Team Pics and Why we choose Alphablox

Gilbert on Wednesday, February 22, 2006 1 Comments

Designing and implementing a business intelligence programme

When implementing a BI programme one might like to pose a number of questions and take a number of resultant decisions, such as:

* Goal Alignment queries: The first step determines the short and medium-term purposes of the programme. What strategic goal(s) of the organization will the programme address? What organizational mission/vision does it relate to? A crafted hypothesis needs to detail how this initiative will eventually improve results / performance (i.e. a strategy map).

* Baseline queries: Current information-gathering competency needs assessing. Does the organization have the capability of monitoring important sources of information? What data does the organization collect and how does it store that data? What are the statistical parameters of this data, e.g. how much random variation does it contain? Does the organization measure this?

* Cost and risk queries: The financial consequences of a new BI initiative should be estimated. It is necessary to assess the cost of the present operations and the increase in costs associated with the BI initiative? What is the risk that the initiative will fail? This risk assessment should be converted into a financial metric and included in the planning?

* Customer and Stakeholder queries: Determine who will benefit from the initiative and who will pay. Who has a stake in the current procedure? What kinds of customers/stakeholders will benefit directly from this initiative? Who will benefit indirectly? What are the quantitative / qualitative benefits? Is the specified initiative the best way to increase satisfaction for all kinds of customers, or is there a better way? How will customers' benefits be monitored? What about employees,... shareholders,... distribution channel members?

* Metrics-related queries: These information requirements must be operationalized into clearly defined metrics. One must decide what metrics to use for each piece of information being gathered. Are these the best metrics? How do we know that? How many metrics need to be tracked? If this is a large number (it usually is), what kind of system can be used to track them? Are the metrics standardized, so they can be benchmarked against performance in other organizations? What are the industry standard metrics available?

* Measurement Methodology-related queries: One should establish a methodology or a procedure to determine the best (or acceptable) way of measuring the required metrics. What methods will be used, and how frequently will the organization collect data? Do industry standards exist for this? Is this the best way to do the measurements? How do we know that?

* Results-related queries: Someone should monitor the BI programme to ensure that objectives are being met. Adjustments in the programme may be necessary. The programme should be tested for accuracy, reliability, and validity. How can one demonstrate that the BI initiative (rather than other factors) contributed to a change in results? How much of the change was probably random?.

Gilbert on Tuesday, February 21, 2006 0 Comments

BI: Key Performance Indicators

BI often uses Key performance indicators (KPIs) to assess the present state of business and to prescribe a course of action. More and more organizations have started to make data available more promptly. In the past, data only became available after a month or two, which did not help managers to adjust activities in time to hit Wall Street targets. Recently, banks have tried to make data available at shorter intervals and have reduced delays. The KPI methodology was further expanded with the Chief Performance Officer methodology which incorporated KPIs and root cause analysis into a single methodology.

KPI example

For example, for businesses which have higher operational/credit risk loading (for example, credit cards and "wealth management"), A large multi-national bank makes KPI-related data available weekly, and sometimes offers a daily analysis of numbers. This means data usually becomes available within 24 hours, necessitating automation and the use of IT systems.

Gilbert on Tuesday, February 21, 2006 0 Comments

BI History

An early reference to non-business intelligence occurs in Sun Tzu's The Art of War. Sun Tzu claims that to succeed in war, one should have full knowledge of one's own strengths and weaknesses and full knowledge of one's enemy's strengths and weaknesses. Lack of either one might result in defeat. A certain school of thought draws parallels between the challenges in business and those of war, specifically:

* collecting data
* discerning patterns and meaning in the data (generating information)
* responding to the resultant information

Prior to the start of the Information Age in the late 20th century, businesses sometimes took the trouble to struggle to collect data from non-automated sources. Businesses then lacked the computing resources to properly analyze the data, and often made commercial decisions primarily on the basis of intuition.

As businesses started automating more and more systems, more and more data became available. However, collection remained a challenge due to a lack of infrastructure for data exchange or to incompatibilities between systems. Reports on the data gathered sometimes took months to generate. Such reports allowed informed long-term strategic decision-making. However, short-term tactical decision-making continued to rely on intuition.

In modern businesses, increasing standards, automation, and technologies have led to vast amounts of data becoming available. Data warehouse technologies have set up repositories to store this data. Improved ETL and even recently Enterprise Application Integration tools have increased the speedy collecting of data. OLAP reporting technologies have allowed faster generation of new reports which analyze the data. Business intelligence has now become the art of sieving through large amounts of data, extracting information and turning that information into actionable knowledge.

In 1989 Howard Dresner, a Research Fellow at Gartner Group popularized "BI" as a umbrella term to describe a set of concepts and methods to improve business decision-making by using fact-based support systems. Dresner left Gartner in 2005 and joined Hyperion Solutions as its Chief Strategy Officer.

Gilbert on Tuesday, February 21, 2006 0 Comments

Bi Software Types

People working in business intelligence have developed tools that ease the work, especially when the intelligence task involves gathering and analyzing large quantities of unstructured data.

Tool categories commonly used for business intelligence include:

* AQL - Associative Query Logic
* Scorecarding, Dashboarding and Information visualization
* Business Performance Management
* DM - Data mining
* Data warehouses
* DSS - Decision Support Systems
* Document warehouses
* EIS - Executive Information Systems
* MIS - Management Information Systems
* GIS - Geographic Information Systems
* OLAP - (Online Analytical Processing) sometimes simply called "Analytics" (based on dimensional analysis and the so-called "hypercube" or "cube")
* Text mining

Gilbert on Tuesday, February 21, 2006 0 Comments

BI Technology

Some observers regard BI as the process of enhancing data into information and then into knowledge. Persons involved in business intelligence processes may use application software and other technologies to gather, store, analyze, and provide access to data (also known as business intelligence). The software aims to help people make "better" business decisions by making accurate, current, and relevant information available to them when they need it.

Some people use the term "BI" interchangeably with "briefing books" or with "executive information systems". One can regard a business intelligence system as a decision-support system (DSS).

Business performance management offers software-oriented business intelligence systems that some see as a new generation of business intelligence, though most people in the field use the terms interchangeably.

Gilbert on Tuesday, February 21, 2006 0 Comments

BI Business Processes

Organizations typically gather information in order to assess the business environment, and cover fields such as marketing research, industry or market research, and competitor analysis. Competitive organizations accumulate business intelligence in order to gain sustainable competitive advantage, and may regard such intelligence as a valuable core competence in some instances.

Generally, BI-collectors glean their primary information from internal business sources. Such sources help decision-makers understand how well they have performed. Secondary sources of information include customer needs, customer decision-making processes, the competition and competitive pressures, conditions in relevant industries, and general economic, technological, and cultural trends. Industrial espionage may also provide business intelligence by using covert techniques. A gray area exists between "normal" business intelligence and industrial espionage.

Each business-intelligence system has a specific goal, which derives from an organizational goal or from a vision statement. Both short-term goals (such as quarterly numbers to Wall Street) and long term goals (such as shareholder value, target industry share / size, etc) exist.

Gilbert on Tuesday, February 21, 2006 0 Comments

The BI Landscape

The phrase business intelligence (BI) may refer to: (1) a set of business processes for collecting and analyzing business information. (2) the technology used in these processes, and (3) the information obtained from these processes.

Source: Wikipedia (open original source)

Gilbert on Friday, February 17, 2006 0 Comments