Is It Time for Business Intelligence?

In recent times we have been facing new challenges such as process re-engineering, 2000, ERP (enterprise resource planning), more recent business intelligence, balanced scorecard, CRM (customer relationship management), SCM (supply chain management) between other acronyms but surely each and every one of them had and have their justification to break into the coveted market of information technologies.

In the following lines I will try to find the answer to the question of business intelligence.

Business intelligence refers to the grouping of granular information for distribution to the directors of the business lines in order to find among other things for example, sales trends, consumer habits and metrics to define the performance of the company and to generate an action.

Many solution providers have launched fabulous tools including Oracle, IBM, Microsoft, SAP, Cognos, Business Objects to name a few not necessarily in order of importance and which are best known in the local market and clear is that investments are not cheap considering the economic crisis and its earlier investments in ERP’s and 2000. These solutions cover much of what the concept entails.

But why now is the time for business intelligence?

I think companies have become more analytical than before due mainly to three impacts that companies have suffered in the way of addressing problems and finding solutions:

• Process Re engineering.
• ERP’s and embedded systems.
• Competitive business line and ready.

Re-engineering has taught us to use metric and make a constant assessment of the results, the ERP and integrated systems have allowed us to have the power to take the pulse of the company and verify real-time performance and ultimately the competitive labor market has allowed employees to have better prepared and less traumatic relationship with information technologies.

The business lines have been mainly this impact and this has allowed them to evolve. They have spread the good management practices and do not by intuition but backed metrics and acute analysis of trends, patterns, behaviors, monitor the critical control factors, and so on.

Found in lines of business, employees who have completed specialized courses, masters, MBA (master of business administration), or people who have gone through profound processes of change using information technology and customer profiles for analytical excellence of a solution business intelligence.
Business Intelligence offers for this new business line access to large volumes of information that will answer selected questions, which may be presented in very sophisticated ways without the intervention of programmers and / or systems analysts.

It is obvious that if your organization does not have a business line ready for this challenge, this experience becomes a nightmare or perhaps a “opportunity” to promote another acronym of many that will appear in this dynamic market of information technologies.

Defining the Business Intelligence For Security Evaluation

Most companies today particularly the business owners are more aware about data warehousing than business intelligence. For them the latter term is a relatively new phrase. While data warehousing is concerned about gathering data and integrating them across several business systems, business intelligence is quite the same. The only difference is that the BI is more focused on how you can use the integrated data so that you can make wise and valuable decisions. At this instant, it cannot be denied that security for the data is one of the main concerns. This is why there is a need to make use of business intelligence for security evaluation.

Numerous stories about data leakage have made it into the news headlines today. If you do not want your company to get involved in such occurrence, you are required to take helpful and effective measures. This way, you can ensure that the business transactions are easily handled and employee efficiency is at its best. Information technology workers and developers need to balance security and the need for critical data, which will be used within the organization.

Security evaluation is done regularly by companies in order for them to securely think that the data that they contain in their systems are in perfect order and protected. Security evaluation BI gives them this assurance that they have they are protected against data leakage. Typically, the information that they have gathered are distributed through the corporate intranet or through email. Regardless of the means of distribution, one is not entirely safe to think that the data that have been dispersed to the right people are only read by them. This is why business intelligence systems are available and they enable the organization to secure their data.

There are many methods of using the business intelligence technology for security evaluation. One approach is through surface area reduction, wherein the system being used will disable the unused components. This method reduces the chance of letting the viruses as well as hackers enter the corporate system. Another useful feature is authentication. Since you only want authorized persons to get within the system, authentication helps you ensure that this is being met. On the other hand, you can set your system to only permit them by creating passwords for the file and to the whole intranet connection. This way, unpermitted personnel will not be able to get within the system by any means.

Another way to guarantee that security of data is working efficiently is to check on the responsible component for the transmission of the data or information across the network. SSL encryption is essential as this secures communication for the user and the web server. You should not also neglect the importance of evaluating the communication security between the web server and the database.

As you gather more and more sets of data everyday, you will most likely think that it is impossible for you to ensure the safety of the information. However, with proper development of the business intelligence for security evaluation, you will be able to handle mountainous data for your corporate intranet.

Beginners’ Guide to Business Intelligence Solutions

Current Condition of the Business Intelligence Tools Market

The sustained interest in Business Intelligence applications has driven large corporations, offshore software development centers as well as custom software development companies to focus on developing a wide range of Business Intelligence Tools suitable for each and every industry. The use of Business Intelligence tools in key industries from aerospace to iron and steel has also increased in recent years due to the uncertainty in global markets. Currently available tools including the Microsoft Business Intelligence software include numerous paid, freeware as well as open source and proprietary software, which are often customized by a custom software developer to suit the requirements of a specific client. Some of the additional categories of Business Intelligence Tools are discussed here and these constitute only a few of the business intelligence reporting tools commonly utilized by the enterprise.

Data Mining

Data mining combines key elements of statistics and computer science with the objective of identifying patterns in large data sets. Currently implemented data mining methodology includes various elements of database systems, statistics, machine learning and artificial intelligence to deliver actionable intelligence to managers, decision makers and data analysts in an enterprise. Apart from the analysis of the available raw data, additional operations performed by data mining process include online updating, visualization, discovered structure post-processing, complexity considerations, metrics to determine interest as well as data management. Data mining is distinct from information processing or large-scale data analysis as the process is based on “discovery” i.e. the detection of something new. As data mining deals with large data sets, various automated and semi-automated solutions are available to carry out the task. Data mining applications developed by any software development company focuses on performing the following tasks- anomaly detection, association rule learning, clustering, classification, regression as well as summarization. Current business applications include data mining in applications related to customer relationship management, determination of successful employee characteristics using HR department data, identification of customer purchase pattern by the marketing department as well as much more. Leading companies engaged in providing data mining tools for use in business intelligence reporting include Extra-Data Technologies, Clarabridge, Versium Analytics, emanio and Polygraph Media.

Data Warehousing

Data Warehousing in simple terms refers to any database utilized for reporting as well as analyzing enterprise data. The data in an enterprise is usually obtained from all over the organization including the HR, Marketing, Sales, Customer Support, Warehouse, administration departments. In some cases, the raw data may undergo a small degree of pre-processing prior to being used for reporting in a Data Warehouse. A traditional data warehouse (a warehouse operating on the extract-transform-load mechanism), houses the key functions by using separate staging, integration and access layers. The staging area stores all the raw data obtained from various enterprise-wide sources. In the integration layer the raw data stored in the staging area is integrated to transform it into a form suitable for analysis and stored in the data warehouse database. The data stored in the data warehouse database is arranged in hierarchical groups, which are accessible by the user through the access layer. Each data warehouse is often subdivided into data marts, which store subsets of the data integrated in the warehouse. The key objective of a data warehouse is thus to store data in a format suitable for analysis by the user using various techniques including OLAP and data mining.

The earliest data warehouses used by an organization were offline operational data warehouses. In these warehouses, the data was updated periodically (fortnightly, weekly or monthly) from operational systems and stored in a report-oriented format. In the next stage of data warehouse evolution, offline data warehouses came into existence. In offline data warehouses, the data was updated regularly from operational systems and the structure of the stored data was designed to aid the reporting process. The offline data warehouses later evolved into Online Integrated Data Warehouses, which updates the data in the warehouse in real-time by recording every transaction performed on the source data. Further evolution of data warehouses has resulted in the creation of the integrated data warehouse, which compiles the data obtained from the various departments of the enterprise to provide users with real-time access to actionable intelligence from all over the organization. Leading data warehousing solutions companies include Accenture, IBM, Igate and Infobright.

Decision Engineering

Decision Engineering is defined as a framework, which unifies various leading practices in the field of enterprise decision-making to improve the overall decision-making procedure by providing a structured approach. The decision engineering process is designed to overcome problems resulting from a “complexity ceiling” of the decision-making process. This “complexity ceiling” usually results from a mismatch between the complexity of a particular situation and the sophistication of the decision-making procedure being implemented. Decision engineering acts as a framework for providing advanced analytic techniques to a non-enterprise user while simultaneously integrating machine learning and inductive reasoning techniques to streamline the organizational decision-making procedure. The use of Decision Engineering as a business intelligence tool by enterprises is still in its infancy and further development would be required before decision engineering develops into a viable business intelligence reporting tool.

Reporting and Querying Software

Reporting and querying software are designed to provide users with access to the data stored on enterprise databases subsequent to submission of user-queries. Such tools are designed to provide a logical format to the available data sets to support enterprise-wide data accessibility as well as speed-up the organizational decision-support process. Currently, various open source business intelligence tools as well as commercial business intelligence reporting software are developed by software development companies all over the world. Some of the leading reporting and querying tools are mPower, Zoho Reports, Cognos BI, GNU Enterprise and JasperReports. Many offshore software development companies in India also provide customized versions of reporting and querying software to streamline the overall enterprise-wide decision making process.

Spreadsheets

A spreadsheet is defined as an interactive computer program, which allows the analysis of available information by use of a tabular format, which originated from the use of paper-based accounting spreadsheets. On a spreadsheet, users can modify the values in each cell of the spreadsheet and are now used widely by the financial sector as a replacement of paper-based accounting methods. The digital spreadsheets allow users to automatically calculate values after making modifications to the available data as and when necessary. Apart from the standard arithmetic calculation support, currently available spreadsheets also features support for a wide range of statistical and financial operations built into this commonly used business intelligence tool. Spreadsheets are probably the most widely used and easily available among a wide range of proprietary and open source business intelligence tools. The first spreadsheet introduced for a micro computer was Visicalc, which was overtaken by Lotus 1-2-3 at a later date. Currently Microsoft Excel, available as part of the Microsoft Office Package, is the leading spreadsheet solution utilized by enterprises all over the world.

What Exactly is Business Intelligence?

OLAP is that piece of the tool set that provides Dimensional Analysis, enabling huge volumes of data to be efficiently made available for exploration in a large variety of formats and arrangements.

The repository of high-volume data and the special methods for designing its storage was given the title of “Data Warehousing” (DW). Within the DW, a representation technique called “Dimensional Modeling” evolved, which is aimed at economic, context-based access (querying) of the immense tables held in the DW database.

Once the data has been captured and arranged in this way, through a process known as “Extract, Transformation and Load” (ETL), it can be passed through a further stage of processing that generates a “Cube”.

The Cube, in this context is actually another highly optimized form of storage in which the Dimensionally Modelled data can be pre-aggregated and cross-mapped for efficient retrieval and presentation to the user, who can enjoy parsing data at many levels of summarization moving quickly between almost limitless varieties of analysis.

Activities such as setting up multi-dimensional charts of data summary (known as “slicing and dicing”) or moving to lower levels of detail and back again to highly summarized versions (known as drill-down and drill-up), using tools to create graphical representations of the Cube data, with a great many formats from which to choose.

Employing yet other tools to perform sophisticated analyses, whereby trends and anomalies buried deep in the data may be discovered, understood and exploited (a technique called “Data Mining”). Data Mining models are created and refined to become sensitive to and resonant with the data patterns and can themselves be used to generate forecasts of future trends and movements within the tracked data. A veritable gold mine of such gems lies hidden and largely unexplored in the “exploding” mountains of data that have accumulated in companies since the price of storage came tumbling down.

It seems that IT organizations have been hanging onto data, keeping it in cold-storage, knowing that there will come a time when it will be of benefit. This is analogous to the hopefuls who upon departing this world, have their brain frozen, awaiting the emergence of technologies that can bring it back to life, perhaps with an artificial body. Business Intelligence is the technology that allows companies to unfreeze their data assets, bringing them back to a much more useful life than before. A New Era for Information Usage?

Early in the eighteenth century, inventors were making new discoveries about heat, energy and motion. There quickly evolved coal-fired, steam-driven locomotion (railways) and pumping engines (for the mines) and giant power plants for making every machine in a factory turn and churn incessantly. Spinning cotton, weaving cloth, cutting and shaping iron and then steel. The Industrial Revolution was born. Mills and factories sprung up all across the coal-rich fields of Northern England (this writer’s birthplace – although a little later).

From their long heritage of back-breaking land work, people seeking to earn a regular (monetary) income flocked to grasp the many new (but equally back-breaking) factory jobs that emanated from the urban sprawl of gleaming red-bricked labyrinths, that housed these awesome machines. Industrial empires were spawning all over and wealthy (already) magnates-to-be, stepped up to invest, build and rule over them.

What did they think of Business Intelligence? Of course, it seems unlikely that the term would ever have been uttered back then but, business empires had to managed somehow. If you could see those monolithic structures and enjoy the experience of visiting them, still churning and clunking, you may notice that almost every square foot of factory space was given over to production or storage of raw materials and finished goods. No room for desks and filing cabinets and, of course, no information technology; not even a telephone!

In one corner of the giant mill, you will see a well appointed office (where the owner would be found most of the time) and one or two nearby, less auspicious areas, being the workplaces of a couple of clerks, whose job was to record all the transactions of the business. Keepers of great leather-bound volumes of hand-written fiscal matters, committed to parchment but rarely revisited. So where was the “Decision Support System”? Where were the “Executive Information Systems” and “Balanced Score Cards”?

It was all there; all that was needed in those horse-drawn days, where real business took place between the various well-heeled mill owners over a mug of coffee or a mulled ale at some local tavern, gentlemen’s club or city-based mercantile gathering hall. The mill owner was kept informed of the production issues, inside his work-house, by visits from the foreman and kept his business knowledge up to scratch by his time spent over the tablecloths of his privileged meeting places. Intelligence was handled by “word of mouth”. Business deals were a handshake, followed by a letter, days or weeks later.

After the initial gold rush of mechanization, little changed for a long time; at least in terms of administration methods. Only after a slow but gradual increase in the number of non-production workers and the (mostly) record-keeping tasks they performed, would another unannounced “giant leap forward” occur, to irreversibly revamp the business scene once again.

Hail, Data Processing Due to regulatory requirements, statutory accounting practices and other external demands, together with a burgeoning management’s appetite for information, the ever-growing office spaces were becoming jammed with bursting-at-the- seems filing cabinets, filled with all manner of records of the company’s actions, transactions and anything else that mattered. All typed-in-triplicate, carbon-copied and filed in strict order (ready to be retrieved and hand-altered or joined by an extension or superseding entry.

Hot, clattering, manufacturing machinery had ushered in the Industrial Age and hot, clattering data processing machinery would now usher in the Information Age. Tabulators, card punches, paper-tape punches and prattling line printers were among the first commercially successful data processing machines. Rapidly progressing into electronic mainframe computers, humming, or even whistling musically (but still quite hot) and requiring huge rooms for their banks of hand-threaded core-memories (as much as 8 Kilobytes per cabinet), and looms of backplane wiring to connect central processor’s thousands of discreet components, soldered to hundreds of Bakelite circuit boards.

Strangely, this great revolution of number-crunching, heat-belching behemoths did little to shake up the world of business. Large corporations would quickly shell out millions for their first pride-and-joy, accompanied by the odd educational institution, here and there. However, vast swathes of less well endowed organizations held back, presumably seeing no threat of extinction as the consequence of not joining in the party for the second great era of industrialization.

Well maybe it is not so strange. The astute leaders of small to medium sized businesses (SMB’s) not known for “leaping before they look”, should be expected to play wall-flower, at least until the proposition looks sound, justifiable and absolutely necessary for survival. Today though, a mere sixty years on, it is hard to find any kind of business, of any shape, size or ethical standing, that does not have heavenly amounts of computing power, at every fingertip.

Bigger, faster, cheaper, more. So the years went by at the “speed of thought”, everyone got onboard and computer systems became as common in the workplace as steam-pipe
leaks, machinery-induced deafness and finger blisters had become in the cotton mill.

Actually, the “Technology” part of “Information Technology” (the “T” in IT) has come an incredibly long way since the days of machines peering through holes in cardboard (which, incidentally, was first conceived of by Industrial Revolution luminary, Jacquard, the inventor of the all-important weaving loom that bears his name).

Some software of today is also astronomically more advanced than that of the mid-twentieth century. Lamentably, it is, however, the “I” in IT that has not kept pace with the advances of electronics and related cost-performance ratios.

With some exceptions, corporate use of computers has essentially become locked into the business of record keeping; frozen solid in the first great ice-age of non-progressive wheel-spinning, running faster to stand still, quagmire, where huge budgets evaporate, just trying to keep up with the avalanche of necessary upgrades and replacements.

Is that the Cavalry I hear?

Having painted a grim picture of stagnation and nil return on investment, we have paved the way for the trumpeters and knights in shining armor. So the cost of storage has come down dramatically, the data we are holding there has ballooned dramatically, now must be the time to do something with it, dramatically.

Instead of just “record keeping”, let’s use all this computing power and endless data in ways that can make us better at what we do. How about introducing software that performs large-scale, sophisticated analysis. How about using that sophisticated analysis to help us make better decisions. How about using improved decision making to choose a better direction to go in and better direction to improve marketing efforts, customer experience, product investment, vendor selection, volume prediction, price setting, etc.

Let’s just call this whole new leap forward “Business Intelligence”.

Get more intelligent about business by seeing more clearly what we have done and what has been happening around us; by predicting where trends are heading and do all this by exploiting data we already have, tools we already own and brains that have not yet been put into deep freeze.

This all sounds good. Lets get started, “as soon as the movement hits critical mass”.

IS there anyone out there already using BI?

When the first great era of commercial computing began, there were early adopters and late adopters. The early adopters paid for all the R&D (as usual) and the tail-draggers paid with loss of market-share, employee job satisfaction and investor confidence. Well, not really; business and consumers were not so hurried, cost conscious or quick to change horses back then.

Today is a different story, however. Deals are canceled at contract signing, shoppers abandon their carts at the check-out, construction is halted on the first foreclosure and stock market indicators have not seen a flat line in years. Panic is the normal state-of-rest.

Businesses sink quickly and everyone is hoping that the next object that floats by will have an outboard motor, wings and booster rockets attached. One such vehicle is that broad set of capabilities currently flying under the banner of Business Intelligence.

Many companies have made a leap of faith and invested in a BI initiative. For some of those entities, valuable gains have been achieved. For others, the project has been fruitless, hard lessons learned and second attempts made from a different approach.

Compared to the early data processing efforts, today’s BI ventures are light years more advanced and equally more challenging. The potential for success is there for all qualified entrants and many have proved the point. Eventually, the deployment of BI will be as ubiquitous as the first generation of applications.

Just as every organization has implemented “passive” record-keeping applications of some sort or another, there will be a time when most will also have “active”, even “thinking” intelligent software that examines data, sniffs out issues, evaluates propositions, recommends actions and monitors results. If you detect a difference in those two scenarios, you are understanding the meaning of Business Intelligence.

There was a time when computers were depicted in entertainment media as futuristic and the stuff of science fiction. Now we can smile at all of that and, yes, there are differences between what novelists and screenwriters created and the more mundane, however clever, computers that support every aspect of our lives today.

Don’t forget, however, that the likes of HAL, C3P0 and R2D2 are seen in laboratories where artificial intelligence and other far-out technologies are constantly making progress. In our business world, we are not looking to replace people with thinking software, but with BI we can get people thinking better (with software).

BI may not be required or mandated for every type of organization; nor is it for the faint-of-heart; nor is it for the uninitiated (i.e. Those not understanding the issues). The separate MeasureGroup™ publication “Who needs BI?” can help an organization decide if it should, or should not, be looking at a BI initiative.

A summary of Business Intelligence

The following panel contains a summary of Business Intelligence in the form of a bullet list of the most significant attributes generally being assigned to this new but not-so-new technology that is going to be recognized one day as the “second great era of computing in business”.

Summary of the key aspects of Business Intelligence:

- Leveraging Data Assets to glean Insights otherwise unavailable
– Exploring Business Analytics in an almost endless variety of ways
– Gaining Competitive Advantage thru the Power of Knowledge
– Seizing Opportunities to improve Status and Profitability
– Enhancing Business Agility – First to Start – First to Finish
– Using Intelligent Questions to generate Intelligent Answers to generate Intelligent Questions…
– Enabling Proactive Management to replace Reactive Damage Control

In the early days of computers, many did not see a use for them. That was because they did not yet understand their capabilities. BI is at that same point now. BI is being enabled by a new set of software tools and technologies that are continuing to evolve.