Accelerating Data Governance for the New Enterprise

As Enterprise Business Discovery momentum has increased, the need for QlikView customers to describe data consistently and then reuse it to speed up deployment of additional applications has grown. To expand the use of QlikView’s Business Discovery platform, a metadata intelligence solution will help IT departments to know what data is being used and how it is being used (data lineage), while ensuring consistency and appropriate reuse of common data definitions (data governance).

“With this acquisition we are taking Business Discovery to the next level, offering a new breed of rapid, iterative metadata intelligence that delivers control at the core and flexibility at the edges of an organization,” said Anthony Deighton, QlikTech Chief Technology Officer.

How it Works: Descriptive Rather Than Prescriptive Approach

With the practical data governance as-you-deploy approach, customers describe data consistently as they build QlikView apps rather than being locked into doing it all upfront with a prescriptive semantic layer.

With the QlikView Expressor active metadata intelligence solution, customers can:

• Capture and manage the semantics of data while building QlikView applications to efficiently reuse data definitions
• Deploy quickly across the enterprise by establishing a repeatable and consistent view of common business and data definitions
• Provide users and IT with increased confidence in data through data lineage analysis
• Realize value from ‘big data’ by handling large volumes of diverse information sources
• Enhance QlikView’s position at the core of information architecture by addressing all data flow requirements into and out of QlikView

“Expressor fits squarely in our acquisition strategy. We are acquiring complementary, tuck-in technology that will enhance the value we provide to our customers as we further develop and bring to market these solutions. We are also adding more than 20 outstanding people, primarily software engineers, expanding our R&D skill set,” said Lars Björk, Chief Executive Officer of QlikTech.

Product Availability

As Expressor had developed integrations to QlikView as a partner, the QlikView Expressor Server is available immediately in standard and enterprise versions. More information can be found on QlikTech’s web site and similar to QlikView, users can try the solution with a free download.

Future product roadmap and integration plans will be introduced over the coming months. Download a fully independent & in-depth evaluation of QlikView in the BI Software Survey Report.

WalMart has made  their suppliers completely responsible for the replenishment of products, informed by WalMart’s management system. The vendors are able to replenish the products at the right moment. Once the products are sold at the counter of WalMart, the replenishment process checks for stock levels falling below a certain value. Walmart is thereby the leader in Commercial Big-Data applications.

Buzzcapture: The algorithms of this business sort online conversations about clients such as ING and Vodafone based on relevance, and can even estimate whether conversations are angry or happy. It thereby often knows disturbances before its clients do.

Erasmus MC:The Erasmus University Medical Center Rotterdam works with DNA sequencing techniques, which can provide almost one and a half terabytes of information about only one tumor. It has developed a data model which has significantly speed up the response time in gathering this information. This makes cancer research at the Eramus MC much more efficient than before.

Cablecom: By analyzing the timing of the subscription cancellation of Cablecom (a telecommunications company), it has been able to reduce the number of cancellations in one year from 20 to 5 percent by offering clients a better deal when they might be contemplating canceling their subscription.

IBM: A selected group of drivers are testing IBM’s ‘Traffic Prediction Tool’, an app which uses GPS-data on the drivers’ driving habits, which can be personalized to give advice for the optimal route to their desired destination.

Rolls-Royce: this company has attached sensors to its engines, which relay real-time performance data to its central database using  ETL software. The company is now able to predict accurately when an engine needs repairs or maintenance.

Li&Fung: this Chinese supply-chain operator is one of the largest in the world, and their real-time processed transaction information means they are a very accurate estimator for economic development. Investment analysts gladly pay for this kind of information.

Equens: together with the Fraud Detection Expertise Center, Equens, a payment processor, has developed a system which analyzes transactions with lightning speed so as to detect the location of the skimming of bankcards, and also blocking these skimmed bankcards with immediate effect.

Capital One: This credit card company has developed algorithms which use a ‘predictive optimization engine’, based on previous website visits, which can estimate the social rank and income of a Capital One website visitor, thereby advertising only certain deals to them.

Visa: its use of novel and highly effective software has meant that it has been more efficient in managing its data streams, by decreasing the time taken to analyze all its transactions from one month to 13 minutes using the new Hadoop system from Apache.

Kaggle: a start-up which organizes competitions whereby participants must make extraordinary predictions by analyzing large data sets using Business Intelligence software solutions. This increases the incentive for companies to analyze their data efficiently.

Nestlé: much of its data about clients, suppliers and resources was outdated, incomplete and even incorrect or had duplicates. By using new information systems to clean up this mess, Nestlé has saved an estimated total of one billion dollars the year.

Please let us know which company in your view is the smartest and why.

What is true business intelligence?

In our view it’s running your business better using key information about your processes, your clients and the market. To be able to do that you should gather all kinds of data from a variety of source systems inside and outside your company network, integrate the data and transform it into information to produce insights in such a way that we can speak of ‘intelligence’. Each company has it’s own intelligence which can bring a real competitive advantage, allowing companies to swim in the profit pool.

What is a cloud?

A cloud is an infrastructure of hard- and software that can be used for a period of time. You may want to use more disk storage, give more users access to the applications or use more memory. Or maybe at some time you want to drop a group of users, which does not pose a problem with the cloud concept. With your applications in a cloud, it should be really simple to scale up or down. Often you only have to pay for the usage, which can be a real advantage.

There are various types of clouds including; the private cloud and the public cloud. In the public cloud every user uses the same business intelligence software solution, the same version and has the same standard indicators and reports. In this type of cloud there is often very little space for customization as it comes down to the data that can be stored, the transformations and the key performance indicators. If you want high customization for example you should extract data from a source system that other users in the cloud don’t have. This means you should move to a private cloud. In a private cloud, which is almost the same as buying a virtual or dedicated private server from your hosting partner, which we are all familiar with, some of the advantages of being in the cloud will disappear. In a private, highly customized cloud, scaling up isn’t that easy (compared to the scalability of a public cloud), whether it is deployed within the company’s firewall or hosted by a third party.

Tap water and BI in the cloud

Cloud solutions like BI in the cloud are often compared to tap water, at least it is often visualized that way. The vendors are marketing their offerings of BI in the cloud as: just turn on the tap and ‘drink the intelligence’. Maybe it tastes good for a while, but what competitve advantage will this solution really bring to your company if your competitors can do exactly the same? In our view true business intelligence can’t really be in the public cloud. In addition, who likes the idea that someone else is managing their brain?

“The only way to make money in the Cloud is to have a lot of customers. The only way to get a lot of customers quickly is to give everyone the same configurable application and avoid custom development work. In the Cloud, economies of scale are everything. But BI is largely a custom development effort.” Wayne Eckerson, BeyeNETWORK

Tap water is, on average, 500 times cheaper than bottled water, some people would say, boycot the bottle. Could we say the same about BI in relation to the public cloud? Is it, on average, 500 times cheaper than having your own BI infrastructure? Even if that is true, we don’t think it’s wise to move your company specific intelligence to the public cloud, even if it is possible (there are some really nasty integration, security and compliancy issues to overcome). However, non-specific highly standardized indicators like the sickness rate could be in the public cloud as a data mart. However you may have to ask yourself if that is true business intelligence. So, don’t boycot the BI bottle!

>>>> Contact me for an appointment about BI in the cloud and vendor independent consulting.

In this article we explore the three biggest challenges of using big data and what to do about it: intelligent filtering, outstanding performance and good data visualization. The main question here is if the business intelligence software we are using today is capable of tackling these challenges.

Big data is becoming a serious business

Big data is so to speak hot and it is becoming a serious business. The amount of data may double every two years. The question is does the amount of valuable information double at the same rate? According to IBM”s Mr. Big Data, vice president Rod Smith: ”maybe 90 percent of it is not very useful”. In general, we may assume the more (complex) the data the bigger the dataset and the more difficult it is to derive information from it. We need to manage big data, that’s for sure. The other 10 percent may be of very great value.

But which technologies and techniques can be used in order to be more successful with big data. Does business intelligence software offer a solution? Do we need special analytical tools on top of it? Or is it just filtering the data properly before we load it into our data warehouse or tool?

“You ain’t seen nothing yet” is a saying that is especially true with regard to big data. It’s very difficult to see any piece of information in a very large amount of information. Especially if you’re looking at the wrong items or using tools that are not capable of analyzing big data (everyone has heard of the ‘query from hell’ or reports that run six hours).

Processing and using big data has three big challenges from a technical point of view. Firstly, intelligent filtering. Secondly, outstanding performance. Thirdly, good visualization.

Intelligent filtering

Because big data is really big and there are many applications, you first need to know what you are looking for and what the purpose is. Is it your company name (and all variations, typos) on Twitter or Facebook or blogs? Is it the temperature of your medicines, provided by sensors, in an airplane flying to Japan? Are you looking for the weather conditions in a specific country? Do you need to know what the most likely path is which visitors of your website took before they ordered your product? In some cases you don’t need all the big data, but only a subset. It depends on the type of application you want to build. So, the first step in building a big data application is to know exactly what you are looking for.

Outstanding performance

The Telco’s of this world had a clue how to process big data sets of structured data. But today, a whole new set of difficulties comes up because of the lack of structure in today”s data, the size of it and the speed by which it is generated. Mobile devices, sensors in cars, plains and RFID chips, large scale eCommerce, all generate a lot of data in seconds that is not yet structured enough to store in a (single) relational database.

Few technologies that can handle big data should be considered as part of business intelligence solutions. To name a few: massive parallel processing (see the ETL Tool criteria), cloud computing platforms, distributed databases, grid computing and the Apache Hadoop framework. Sure, filtering first is key, but you can use it only if the rest of the data isn’t relevant at all and the data set you should filter on is stored in a way which supports filtering.

This looks like a ‘Catch 22’ situation: to be able to filter intelligently, normally you should put the data in the database first, but to put the big data in the database you should sometimes filter it first. That is where Hadoop comes into the picture or any of its alternatives: GemFire, MarkLogic, and neo4j. Because of its distributed nature and sophisticated technology it can handle large data sets very well, for fast storage as well as quick retrieval. It can work on pieces of data in parallel. Today, the Hadoop community is working on a data warehouse system (Hive DWH) based on Hadoop technology.

Good data visualization

If the big data is available in a way which can be queried, inside or outside the cloud, the last difficulty is to visualize the data in a proper manner. The main purpose of visualization is to communicate the information clearly and in an effective manner. That means not necessarily the data should always be presented in graphs. Some information could very well be effectively communicated in a sorted plain list or a pivot table. It depends on the purpose (what relations are you looking for in the data set) and the nature of the data.

According to research performed by Cleveland and McGill there is a difference in the accuracy in quantitative, ordinal and nominal tasks (Mackinlay, 1986). Higher tasks are accomplished more accurately than lower tasks. Tasks to perceive different positions in the data rank as best and differences in shapes are the perceived as being the worst. The following table (adopted from Cleveland and McGill) ranks which task (type of graph) is most effective for each data type (quantitative, ordinal and nominal).

Table 1: ranking of encoders by effectiveness; position is for quantitive data the best visualization; shape the least.

But these basic rules are a little bit too simplistic for big data, although they can be useful as basic guidelines. They also gave an implicit warning to be careful when using 3D graphs because volume is not included in the different types of tasks by the top five.

Identifying complex relationships in large data sets should persuade you to use a combined approach using different techniques on top of the guide lines. Simulation and animation (for example showing over time the variation of a multidimensional indicator is one of them. A good example is demonstrated in the following video. Multiple dimensions are shown using color, size and position.

But more concepts and methods can be helpful to visualize the data in the right way. An overview of visualization methods is given here.

Conclusion

To return to the main question, ‘Does business intelligence software provide enough tools and functions to tackle the challenges of big data?’, we must conclude that the BI software vendors are on their way, but may fall short on a few areas, depending on the BI software you are using.

• Large unstructured data sets: BI software may possibly read it well, but they are not doing a great job because of the size and the lack of structure of the data. This may cause real performance troubles despite the fact some tools have advanced In-Memory technology. You should consider using Hadoop technology (or an alternative) and built a data warehouse first by using for example a data integration platform like Informatica or less sophisticated ETL tools. When the big data is in a cube or data warehouse performance shouldn”t be a problem anymore.
• Data visualization: although, a lot of visualization methods can be used out-of-the-box with BI tools, on average they provide between the 15 and 20 types of visualizations, the possibilities of most of the BI software are still quite limited compared to all visualization methods that are available. If you need advanced visualizations, take a look at the list of data visualization software. It can sometimes be integrated with BI software like Trendanalyzer (a Google API), or you may use it on top of BI software or as an alternative.

Last but not least, if your business intelligence platform can handle big data in a proper way, you have the right technology that suites you. But, worldwide there is a shortage of people with deep analytical skills that can make effective use of the big data technology (McKinsey, 2011). So, don”t focus only on technology, consider also the skill side of big data & business analytics.

Download our fully independent & in-depth evaluation of Business intelligence software in the BI Software Survey and see what software matches the requirements for big data best.

Previously only Flash enabled mobile devices could leverage InetSoft’s web-based server application for interactive dashboards and visualizations. Now, non-Flash enabled browsers such as those on Apple devices are served via HTML5 – the new markup Internet markup language that supports rich interactivity. Users of all mobile devices can now utilize interactive controls such as selection lists and slider bars to filter and analyze large amounts of data in an intuitive, compact information delivery system. For BI developers, Style Intelligence allows a develop-once and deploy-on-all methodology to support all end-user devices, whether they are desktops, laptops, tablets or phones.

Other enhancements in this release meet product improvement requests that make work for dashboard and report developers easier and quicker. These include on-the-fly pre-aggregate and post-aggregate computations which enable for instance, charts showing percentages of a total without the extra steps of adding those metrics at the data modeling layer using InetSoft’s data mashup and transformation tools. Another improvement makes remote team development more efficient in multi-tiered support environments such as those run by SaaS providers or multi-national enterprises.

“This product release demonstrates a natural progression for our BI application,” commented Mark Flaherty, CMO at InetSoft. “We focus on making our software user-friendly, and with business users demanding the flexibility of accessing their corporate information on the platform of their choice, we’re meeting that demand. At the same time, we aim to make the lives of IT professionals easier by streamlining the process of mobile BI development. And we pack the release with other enhancements that speed up their workflow and reduce their BI application support overhead.”

Style Intelligence is a full-featured business intelligence solution for dashboard reporting that includes a powerful data mashup engine. End-users get visually compelling, highly interactive access to data, and IT gets a highly customizable, easy to learn and quick to deploy business intelligence toolset and information delivery platform. Data mashup capabilities allow for the integration of disparate data sources, enabling agile development and providing maximum self-service, while the application’s SOA architecture and open standards-based technology make for an ideal embedding and integration-ready application for dashboards, production reporting, and visualization.

Download our fully independent & in-depth evaluation of Style Intelligence in the BI Software Survey Report.

• Ted unveiled the final name for the next SQL Server release: SQL Server 2012. Not really a big surprise.
• In addition the VP disclosed an end to end roadmap for Big Data. Microsoft is going to support the Apache Hadoop platform in 2012.

Microsoft Mobile BI initiatives

Finally, Microsoft is committed to delivering highly interactive and immersive BI experiences across different mobile BI applications & devices to all users wherever they are*. Their approach and roadmap for fulfilling this vision consists of:

• Ensuring existing corporate web based business intelligence solutions run in browsers across iOS and Windows devices in the first half of 2012.
• Delivering great touch-based data exploration and visualization capabilities in a browser on iOS (Apple), Android and Microsoft platforms in the second half of 2012.
• Delivering the best in class rich and immersive experience of the Microsoft BI platform on Windows 8.

* More than 75% of those who voted in a recent Passionned Survey believe that business intelligence will become completely mobile in the near future. See the article ‘The future of business intelligence is mobile’.

Details in the SQL Pass Recap.

To help organizations achieve better business visibility and alignment, Oracle today introduced new releases of its complete, integrated and scalable business intelligence products including Oracle Business Intelligence, Oracle Business Intelligence Applications and Oracle Real-Time Decisions.

The new product capabilities delivered span out-of-the-box iPad and iPhone support, extended OLAP tools and in-memory platform support, enhanced real-time decision management features, new certifications, and more.

Enterprise-Class Analytics and Actionable Intelligence on the Go

The new Oracle Business Intelligence Release 11.1.1.5 introduces support for the iPad and iPhone. This release provides on-the-go access to the complete range of alert, ad hoc analysis, dashboard, reporting, scorecard, “what-if” analysis, and unified relational OLAP (R-OLAP) and multidimensional OLAP (M-OLAP) content of Oracle Business Intelligence.

In addition, users now have the ability to initiate actions and workflows directly from their mobile devices – helping to reduce the time needed to make decisions while enabling a more flexible, agile organization. Oracle Business Intelligence Release 11.1.1.5 content is optimized for use with the iPad and iPhone – without requiring design changes to existing reports and dashboards.

This new product release also introduces extended support for additional data sources including Oracle TimesTen In-Memory Database, Oracle OLAP, Microsoft SQL Server Analysis Services and SAP Business Information Warehouse (BW). Oracle Business Intelligence is a component of the Oracle Business Intelligence (BI) Foundation Suite, which offers organizations a complete, open, and architecturally Business Intelligence solutions. The suite serves every class of user, providing multiple channels of information access, and supporting all enterprise BI requirements.

Enhanced BI Application Mobile Capabilities, User Experience and Performance

The latest release of Oracle BI Applications is built upon Oracle Business Intelligence Release 11.1.1.5 — enabling organizations to take advantage of the platform’s enhanced mobile features, user experience, systems management, performance, and scalability. Oracle BI Applications Release 7.9.6.3 benefits include:

• Alerts, dashboards and reports are available for secure access and interaction via iPad and iPhone to provide organizational visibility, insight and alignment;
• A new user interface featuring a wide range of interactive charting and prompting capabilities, including map visualization options directly linked to spatial data, providing a richer, more intuitive end user experience;
• An enhanced Common Enterprise Information Model with 25 conformed dimensions that provides alignment across the enterprise as well as high performance, federated queries against hundreds of data sources in relational, OLAP, and XML formats; and,
• Integrated system management services to simplify system configuration, testing, deployment, monitoring, and installation of patches to enable continuous availability, with unmatched query performance, scalability, and security.

Oracle BI Applications are complete, prebuilt analytical solutions for Oracle and non-Oracle applications including SAP. Subject areas include Financial, Human Resources, Procurement and Spend, Projects, Supply Chain and Order Management, Contact Center Telephony, Loyalty, Marketing, Price, Sales, Service, and a range of vertical industries.

Optimizing Customer Interactions with Real-Time Intelligence

To better help organizations optimize their customer interactions, Oracle Real-Time Decisions Release 3.1 introduces “Decision Manager,” an application to manage, monitor, refine, and optimize operational decisions across customer interaction channels. Decision Manager enables business stakeholders to collaboratively define closed-loop analytical business logic for delivering optimized customer experiences. Built using Oracle Application Development Framework (ADF), a component of Oracle Fusion Middleware 11g, Decision Manager offers a collaborative and rich user interface for business stakeholders to:

• Author and refine their decision eligibility and targeting logic;
• Search and manage their catalogs of campaigns, offers, products and other enterprise content; and,
• Analyze the results of their operational decisions to discover new insights.

The application also provides role-based access control, versioning, and audit trail to ensure operational consistency and reduce overall cost of ownership. Oracle Real-Time Decisions is a highly scalable service oriented decision management platform for decision optimization. It leverages real-time and historical data, business rules, predictive models, automation, and self-learning techniques to deliver decisions that adapt over time. Its decision services can be embedded in transactional applications across the enterprise to optimize performance of recurring operational decisions.

Oracle Real-Time Decisions is an open enterprise decision management platform, that integrates easily with any customer touch-points infrastructure for web, contact center, email, kiosks and point-of-sale. It is also available pre-integrated with Oracle’s Siebel CRM.

Supporting Quotes

“These new Oracle Business Intelligence product releases build upon the success of Oracle BI 11g and provide customers a wide range of new capabilities that extend intelligence to the iPad and iPhone, offer more powerful visualization, interactivity, performance and scalability features to their ERP and CRM applications, and optimize customer interactions and decisions in real-time,” said Paul Rodwick, vice president of Product Management, Oracle Business Intelligence.

“Oracle continues to deliver new capabilities and enhancements including heterogeneous platform support across Oracle BI Foundation, Oracle BI Applications and Oracle Real-Time Decisions,” said Dan Vesset, vice president, business analytics, IDC. “According to IDC research, worldwide demand for business analytics software continues to grow, and Oracle is positioned to help organizations benefit from the analysis of the vast amounts of data they generate.”

Download our 100% vendor independent & in-depth evaluation of Oracle Business Intelligence in the BI Software Survey Report.

The 2011 Survey now includes for the first time sections on Performance Management, Predictive Analysis (Data Mining) and technical performance issues like use of aggregates and caching. These have been included to help take account of various trends in the market – specifically “Big Data”, the increasing use of management systems like Balanced Scorecard and the interest in trying to predict future performance instead of just reporting what has happened in the past.

Creating successful BI systems is very complex, because different types of companies have different requirements. In our view it would be a mistake to restrict the initial choice to one or two companies just because they have a large market share. Read more in the section ‘BI Software Insights’ or download the Business Intelligence Software Survey.

The acquisition of Cognos supports IBM’s Information on Demand strategy, a cross-company initiative announced on February 16, 2006 that combines IBM’s strength in information integration, content and data management and business consulting services to unlock the business value of information. Integrating Cognos, the 23rd IBM acquisition in support of its Information on Demand strategy, will enable new business insights to be delivered to a broader set of people across an organization, beyond the traditional users of business intelligence.

IBM said the acquisition fits squarely within both its acquisition strategy and capital allocation model, and that it will contribute to the achievement of the company’s objective for earnings-per-share growth through 2010.

“Customers are demanding complete solutions, not piece parts, to enable real-time decision making,” said Steve Mills, senior vice president and group executive, IBM Software Group. “IBM has been providing Business Intelligence solutions for decades. Our broad set of capabilities — from data warehousing to information integration and analytics — together with Cognos, position us well for the changing Business Intelligence and Performance Management industry. We chose Cognos because of its industry-leading technology that is based on open standards, which complements IBM’s Service Oriented Architecture strategy.”

Together, IBM and Cognos will become the leading provider of technology and services for Business Intelligence (BI) and Performance Management, delivering the industry’s most complete, open standards-based platform with the broadest range of expertise to help companies expand the value of their information, optimize their business processes and maximize performance across their enterprises.

The acquisition of Cognos accelerates IBM’s global Information on Demand initiative to unlock the business value of information for our customers. IBM will provide broader reach for Cognos solutions across multiple industries and geographies with a more complete set of offerings, including consulting services, hardware, and other middleware software.

Cognos provides the only complete BI and performance management platform, fully integrated on an open-standards-based service oriented architecture (SOA), and has a strong history of supporting heterogeneous application environments, consistent with IBM’s approach. With Cognos, customers can turn data into actionable insight for coordinated, information-driven decision-making to improve overall performance. Cognos will also extend IBM’s reach further into the CFO office with powerful financial planning and consolidation capabilities.

“This is an exciting combination for our customers, partners, and employees. It provides us with the ability to expand our vision as the leading BI and Performance Management provider,” said Rob Ashe, president and chief executive officer, Cognos. “IBM is a perfect complement to our strategy, with minimal overlap in products, a broad range of technology synergies, and the resources, reach, and world-class services to accelerate this vision. Furthermore, this combination allows Cognos customers to leverage a broader set of solutions from IBM to advance their information management driven initiatives.”

Together, IBM and Cognos will expand IBM’s ability to provide customers with the right information they need when they need it, to optimize operational performance, and to quickly respond to changing market demands. The combination of IBM’s information management technology and Cognos will also help organizations discover new ways to use trusted information spread across their enterprises to identify new business opportunities and significantly reduce the expense and time required to address industry-specific business challenges.

Following completion of the acquisition, IBM intends to integrate Cognos as a group within IBM’s Information Management Software division, focused on Business Intelligence and Performance Management. IBM also will appoint current Cognos President and CEO, Rob Ashe, to lead the group, reporting directly to General Manager, Ambuj Goyal.

Cognos has approximately 4,000 employees worldwide and serves more than 25,000 customers. IBM and Cognos have partnered for more than 15 years, with extensive technical integrations and eight pre-integrated joint solutions already supporting many joint customers, such as New York City Police Department, Blue Cross and Blue Shield of Tennessee, Canadian Tire, MetLife, and Bayer UK.

Other strategic acquisitions in support of IBM’s Information on Demand initiative include Princeton Softech (data archiving and compliance), FileNet (enterprise content management), Ascential Software (information integration), DataMirror (changed data capture), SRD (entity analytics), Trigo (product information management), DWL (customer information management) and Alphablox (analytics).

Business intelligence has guided restaurants on which burgers to add, helped retailers determine which customers to target for upselling and guided sports teams to victory. But the business intelligence arena is changing and its reach is growing. BI is becoming increasingly important to businesses as they try to turn data into information. To whit, Gartner found it to be the number one technology priority for 2007.

“Business intelligence is permeating into all nooks and crannies of the business,” says John Hagerty, an analyst at AMR Research. Whereas business intelligence was largely confined to finance and human resource, the increased offerings and developments mean additional uses. “The number of users BI can touch grows phenomenally,” he says. Increasingly, there will be “more insight into more stuff for more people.”

Here are five key business intelligence trends that are having an impact.

Business Intelligence Trend No. 1: There’s so much data, but too little insight.

Here’s one big reason business intelligence is on companies’ radars: the volume and velocity of information. More data translates to a greater need to manage it and make it actionable. “Everything we use and everything we buy is becoming an information source and companies must be able to figure out how to harness that,” says Bill Hostmann, a Gartner research analyst.

The problem? “Organizations are recognizing they don’t have the information they need to manage the business,” says Hostmann. The data is there, but it’s trapped in different silos and its accuracy can’t be trusted. For example, how information is entered can vary widely from how it needs to be used to make organizational decisions and, all too often, definitions vary from silo to silo. For example, finance and marketing could define gross margin differently, which influences how and what numbers are reported.

Trend No. 2: Market Consolidation Means Fewer Choices for Business Intelligence Users.

Independent business intelligence companies may soon be a memory. First, Oracle bought Hyperion in February. Then in early October, SAP made a bid for Business Objects. That leaves Cognos and MicroStrategy as potential takeover targets, with speculation growing that Cognos will be next.

On the one hand, there may be some advantages to having large vendors in the business intelligence arena. Traditionally, business intelligence is not a top-of-mind investment for companies, but rather a sort of afterthought once the major application decisions were made, says John Hagerty, an analyst at AMR Research. As large vendors integrate business intelligence capabilities, BI will be easier to integrate into that vendor’s applications. Furthermore, investment in business intelligence may become more of a core decision, he says.

One the other hand, as independent business intelligence companies are acquired by the giants, many practitioners and experts worry that “the software provider you’d like to use will end up in the hands of a vendor you don’t want to do business with,” says Hagerty. Moreover, the company that does the acquiring may not fit into your current architecture; competing technical stacks may became an issue, he says. “What I’m seeing is clients determining which vendor they want to use, then the logical question is, Who’s going to buy this company? It’s on everyone’s mind and that uncertainty causes people not to move or to move to an alternative that they think won’t change.” So market consolidation could make it easier to get BI, but users may be left with fewer choices.

Trend No. 3: Business Intelligence Expands from the Board Room to the Front Lines.

Increasingly, business intelligence tools will be available at all levels of the corporation. Operational business intelligence-which brings business intelligence to employees on the front lines-is growing especially fast, industry watchers say.

Boris Evelson, an analyst with Forrester research, says operational business intelligence will include offerings that integrate data and process dashboards, and event-driven systems that initiate a business process based on certain data conditions.

For example, integrating business intelligence into operational processes could allow companies to react faster to changing business conditions, for example, alerting a call center worker to offer a particular promotion or to potential credit card fraud.

Trend No. 4: The Convergence of Structured and Unstructured Data Will Create Better Business Intelligence.

E-mail, memos, voicemail messages and other sources of unstructured data are rich sources of information, and companies and developers are responding by looking for ways to blend structured and unstructured data for better decision making. For example, retailers could add comments and complaints from e-mail and call centers into a BI application to enhance their market segmentation analysis, says Evelson.

Hagerty agrees: “Getting information that’s not in the typical rows and columns is the next logical frontier.” He adds that this trend holds real promise. “This gives people more information to make the right decision,” says Hagerty. People will no longer have to rely on “gut,” but will instead have more information with which to make informed decisions.

Source: InfoWorld