- How is business doing in the sales department? What product is the best sale this quarter?
- Which region will have most sale amount this year? Which region will have worst sale amount this year?
Tampilkan postingan dengan label Business Intelligence. Tampilkan semua postingan
Tampilkan postingan dengan label Business Intelligence. Tampilkan semua postingan
Author: Roger Deng
Overview
Recently some of my colleagues asked me about what kind of business functions should data warehouse support, analytical or operational?
Before I answer that question, let’s review some issues business currently is facing regarding to information requirements. Most companies have many distributed information systems and the business data are scattered everywhere. It is very hard for people to see all the transaction data about his clients at one time, one screen. Data warehouse seems is the only place where could have such detailed, cleansed, integrated and completed information. So how to leverage the existing data warehouse investment to help business to make smart, objective decisions and improve operations efficiency from both analytical and operational needs is another challenge to IT people.
Along with the growth in the use of Business Intelligence and Data Warehousing, the BI industry is also going through a period of significant change. BI is no longer used just for doing strategic and tactical reporting and analysis, but also for driving and optimizing daily business processes and workflows. BI is no longer nice to have but essential to business success.
Analytical Space
Traditional data warehouse usually support analytic functions, which answer following business questions:Operational Space
There is a recent trend to use data warehouse and business intelligence technology to help improve operation efficiency for normal people like salesperson or customer service representative or even customers themselves. The requirement for data is more timely and integrated. Users of this space are looking for the integrated detailed information about certain person like a called customer or a requested client etc. They are trying to answer following type of questions.- What are my most recent transactions?
- Have my medical claim processed or what’s the current status of my claim? Any rejected ones?
- Based on customer’s medical history, what’s the best insurance plan suited for this customer? Any recommendation?
Usually data warehouse access design is based on the data usage and targeting to certain group of business people and their business functions. It is very hard to design a single database to accommodate both of these types of users. So is there a better way to accommodate these two different types of users without big change in your data warehouse architecture?
The answer is yes and absolutely.
Architecture Solution
The data to support both analytical and operational needs are all coming from the same source systems. It is critical for them to provide the same truth from both sides across enterprise reports. In order to reach this goal, we need to provide a solution from architecture so that the data flow to all analytic and operation databases are consistent and could match each other. One of growing trend I have seen is to build a centralized enterprise data warehouse and then feed to different data marts for different purpose. All business rules and derivations are done in data warehouse area. The data marts are sole optimized for user access. Figure 1 shows this architecture in high level.The advantage of this architecture is that the data are extracted once from transaction systems, cleansed once, applied business rules once and integrated in one place. This “done once and used anywhere” strategy helps to remove duplicate efforts and thus save companies time and resources. This also helps to reach the objective of providing a single version of the truth for enterprise use. The data quality could also be controlled and addressed from enterprise level.
Figure 1 – Architecture Solution
Conclusion
Business Intelligence and data warehouse have been evolved and matured enough to support both business analytical and operational needs. How to leverage existing investment is the challenge to any data warehouse architect and IT departments. This paper provides one solution and definitely not the only one. There are many variations of this solution based on each company’s actual data warehouse architecture. An enterprise solution architect should have an open mind and apply the technologies smartly to meet any business challenges.About the Author
Roger Deng has been working in the data warehouse area since 1994. He is currently working as a Enterprise Data Warehouse Architect for a healthcare company. You can reach him by email at. rogerdeng@yahoo.com
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Author: Andy Hayler
The IT industry is fast moving, and is full of people in their twenties and thirties. So perhaps it is not surprising that it does not learn well from past mistakes. Those rather longer in the tooth can permit themselves a wry smile as the industry shows a new fad for “executive dashboards”, “cockpits”, “balanced scorecard applications” and the like. The idea is fine: rather than having to wade through endless reports, senior executives of a company will be presented with a pretty display, like the cockpit of an airplane, showing the critical operational numbers of how their business is performing: sales, gross margins, production quality and such. The more entertaining demos of such products show a mythical executive “drilling in” on a problem area, and immediately identifying an operational problem from the pretty charts that come up, which is then fixed via a swift email to the offending business unit.
Like many fairy tales, this sounds nice, but the reality is somewhat different. I recently met the chairman of a major brewery, and he told me a very different story. He explained that his dashboard has numerous missing business areas and little notes attached to numbers with endless caveats. Why should this be? The problem is not the dashboard applications in themselves; the problem is with actually getting at the underlying data that feeds the dashboards. Those with long memories will recall Enterprise Information Systems (EIS) which were sold to senior executives in the late 1980s on exactly the same promise. How many of those are still around? Those systems failed because it took the same army of analysts who currently produce the nice PowerPoint slides that executives review, to be able to feed the EIS systems that would prettily display the same numbers on the EIS screens. Most people would probably rather scan through a set of well-presented slides than click around on a screen anyway, so no value was added. All the same analysts were employed, plus a few more who had to feed the EIS system, so the systems were mostly quietly retired when the sponsoring executive moved on. The problem is a fundamental one: the information that provides things like gross margin by product, channel and customer is buried away in a multiplicity of separate operational systems: multiple instances of ERP, plus CRM systems, supply chain systems and the many, many other systems that large companies use. It is the multiple sets of business definitions embedded in these multiple systems that cause the problem.
For example, rebates and commission structures may vary by country, potentially distorting revenue figures when you add up net revenues across the globe. Costs are even more complex, with each business unit or country having a slightly different ERP instance, and slightly different ways of allocating back costs. Do you allocate all costs of a business transaction back to the original transaction via some allocation rule, or are some costs held at the country, regional or global level e.g. management overhead, office costs etc? What about marketing costs? Are these allocated back to each business unit, or to each individual transaction or customer account? It is a rare multinational company that can honestly say that these rules are all identical throughout the globe. I have personally worked in two of the largest and most successful global companies, and if I had a dollar for every time I heard someone arguing about whose data was the “right” data in a meeting then I would be relaxing on a beach rather than writing this article.
The reality in large companies is that a small army of analysts apply mind-boggling sets of rules to the data that is sent in from the various business units to iron out these little differences between business units and countries, and so present a moderately coherent view of things at the corporate level. Tools which seemingly reach out directly into the operational systems in these countries and retrieve the data look pretty on demos, but cannot work in practice since they have to resolve the semantic inconsistency between these systems, as well as deal with the very real issue of data quality. Since the average number of “master” definitions of key items like “product” and “customer” in a large corporation is not one, but eleven (according to a recent survey by Tower Group) it can be seen that such an approach is fundamentally flawed.
The usual way to resolve this is to build a corporate data warehouse in which the different source systems feed data that is then automatically massaged (“transformed”) into a single consistent form, reducing the average of eleven definitions to one. However the problem is that these systems are build on shifting sands. When one of the business units reorganizes, or the company acquires another one, this briefly consistent picture is shattered, and traditional data warehouses take weeks or months to restructure if there is a major structural shift in the underlying source data. If there are many sources, then every one of them can change, having a knock-on effect to the data warehouse, and a further effect on all the reporting systems that use the warehouse for source data. It doesn’t matter how pretty your reporting tool can format results, or draw nice graphs for you if the data underlying the report is wrong. The new generation of dashboard products may be cheaper and prettier than the 1980s EIS systems, but the IT industry appears to be adapting a selective memory [not sure of the wisdom of including this – dangerous ground] when it comes to remembering the problems that occurred with just such systems not that many years ago.
Regrettably, tedious issues like inconsistent master data, data quality and brittle data warehouses don’t play well in sales demos, so you won’t be hearing about them any time soon from your dashboard, cockpit or scorecard vendor. Since salesmen can be very persuasive, it looks like there will soon be a new generation of EIS systems built, with entirely a predictable outcome. We will soon see further growth in that old favorite software type, shelfware.
About the Author
Andy is an established enterprise software industry expert and commentator, named a Red Herring Top 10 Innovator in 2002. Andy founded Kalido as an independent software company after originally setting up the software venture within the Shell Group. He became an independent consultant in August 2006.Prior to leading Kalido's spin off from Shell in June 2003, Andy was CEO of Kalido Ltd in January 2001. In previous roles at Shell, Andy led a 290-person global consultancy practice of Shell Services International, and was Technology Planning Manager of Shell UK Oil. Prior to Shell, Andy worked in a number of senior technology positions within Exxon.
A 20-year veteran of data warehousing and integration projects, Andy is a regular speaker at international conferences such as ETRE, Tornado Insider, Red Herring, Gartner and Enterprise Outlook. See his award winning blog www.andyonenterprisesoftware.com for his insights on the industry.
Andy has a BSc (Hons) Mathematics degree from Nottingham University.
Author: Raymond Borhan
With all the rapid changes taking place in the world of Business Intelligence these days, it’s hard to get a grip on just how to tackle your data delivery problems. Should you consider a cloud-based solution? Or SaaS-based? Has the time for an in-memory solution finally arrived? What implications do the rapid changes in BI/DW technology hold for the investments you’re making now? And what if the 6-9 month average time to delivery just isn’t fast enough for your organization’s needs? These are just some of the questions TDWI’s World Conference in San Diego (Aug. 16 – 20th 2010) and its concurrent Executive Summit (Aug 16-18th 2010) promise to address, and the overarching theme which ties it all together is Agile BI.
According to Wayne Eckerson, the secret to success in today’s environment goes beyond just agile methodology. Success he says, also involves adaptability. Eckerson’s keynote speech which will open the conference will therefore focus on a practical framework for creating agile BI environments which can not only respond rapidly to business needs, but have the flexibility to respond to new and unforeseen changes in business and technology environments with minimal pain. Among other things, such a framework, says Eckerson, will help to prevent what has been the nemesis of corporate BI organizations for years – the dreaded growth of shadow systems created by business users for whom the sanctioned delivery system always offers too little too late.
Indeed, in an environment where business needs and technologies are rapidly changing, it’s all about “adapt or perish.” That’s why the second keynote speech at TDWI conference – delivered by Ken Collier of KWC Technologies on Thurday, August 19th – is entitled “The Katabatic Winds of Business Intelligence.” The katabatic winds of Antarctica are among the strongest winds on earth, and require constant monitoring and adaptation for those brave researchers who live on the continent; monitoring and adaptation become key to survival. Collier argues that the rapid changes shaking the world of business and BI technology are no less cataclysmic and require the same degree of monitoring and adaptation by those BI organizations who hope to survive them. With this in mind, Collier will examine emerging agile technologies which are conducive to adaptability – including Cloud and SaaS environments and the no SQL movement.
TDWI’s Executive Conference will elaborate on the themes of adaptability and flexibility with an in-depth look at the hot topics of cloud computing, MDM, and the role these topics play within the agile framework. Featured at the Summit will be the representatives of companies with enviable records of delivering timely analytics for driving business processes, including Eric Colson of Netflix whose presentation - “Radical BI: Moving Fast as the Business Wants” – is, in our opinion, by itself worth the time and costs of attendance.
Of course, as always, building on the topics covered in the keynote speeches and the in-depth presentations will be TDWI’s broad range of course offerings. “There’s always something new” says Eckerson, who also says of this year’s courses “it’s the best line-up of content we’ve ever had.” TDWI promises fully updated material, and at least a quarter of the courses will be covering completely new material. In addition to the core offerings leading to the industry’s most respected certification (CBIP), this year’s courses will include plenty of courses related to the agile theme, and some of the courses of particular interest include:
- BI in the Cloud
- An Agile Method for Data Warehousing
- Architecture and Technologies for Agile OLAP
- Extreme Scoping: An Agile Approach to Data Warehousing and Business Intelligence
- Virtualization Technologies for Tomorrow’s BI in Cloud Environments
About the Author
Raymond Borhan is an editor at BusinessIntelligence.com.
