Cloud computing and mobile internet power boost business intelligence (1)

Our research has found that the current popular tools for mobile business intelligence and cloud computing are not important to meet changing business needs, and that it is important to have reliable information management solutions. The goal that business leaders strive for is to make them more flexible. They need systems that can quickly support changes in demand, to maximize the use of procurement, to enter new markets, or to find new customers. In recent years, "flexibility" has been a hot topic in the field of software research, the current hot topic also appeared in the field of business intelligence.

In some powerful existing business intelligence, we can still see the need for flexibility. The need for rapid access to new insights is contributing to the development of rapid assumption analysis planning tools and memory analysis capabilities. The ability to anticipate emerging needs and risks in advance has stimulated interest in predictive analysis. You may think that mobile transmission, cloud computing and Google type queries will still play a significant role in flexibility, but the < information weekly > Analytical Business Intelligence and Information Management watch shows that these are still emerging concepts that are far from being widely used.

While most business people want business intelligence to be more flexible, they rarely hear about the basics of business intelligence--Comprehensive information management--and they rarely invest in it. Information management includes data discovery, modeling, consolidation and cleanup, and data warehousing optimization--which are both difficult and time-consuming. Often, when it is just beginning to take over existing information, the company buys other companies, which results in the previous work of the IT staff.

Looking at this year's findings, the list of improvements made by business intelligence users has not changed much. Rapid analysis, rapid deployment, and other flexibility-related attributes remain high on the forefront. However, there is a growing view that business intelligence should evolve in tandem with information management.

Over the past two years, respondents to our survey have identified a number of issues related to information management, which have become a major impediment to business intelligence tools throughout the company. The proportion of data quality problems is most in 2009 and 2010 accounted for 55%. , the second of favorite is ease of use, integration and compatibility with existing platforms. In the survey of information management, the main obstacles to success are timely access to relevant reliable data (59%), clean-up, replication, and consistency of data (51%), Data Integration (49%).

Pfizer's program has passed the M&a test.

Peter Green, director of business integration at Pfizer, the pharmaceutical giant, is very clear about flexibility. Green and his team have been involved in a series of Pfizer acquisitions over the past decade, including the 2001 hit takeover of rival Huana Lambort, the 2004 acquisition of a pharmaceutical company Pharmacia and the 2009 takeover of Wyeth. Behind the merged companies are intellectual property, which exists in the form of data, especially in their research laboratories. In each case, the data must be quickly consolidated in order to make the most of the investment.

Most pharmaceutical companies use similar procedures and the same terminology to describe the drugs they develop. However, each company has some discrepancies in the way it defines their information, so consolidation after mergers will be "slow and painful," Green said. The drug data on the company's production line include molecular description, experimental results, status in various control procedures, such as the FDA certification.

Pfizer already knows that integration is not necessarily a lengthy process. Green is dedicated to the development of Pfizer's OneSource platform, which integrates research and development data from different companies, allowing executives to see more details about the billions of-dollar drug development pipeline. Most importantly, this is a very flexible platform that can quickly integrate new data.

The old way Pfizer used to be known as "heavy iron fusion" means to import data from other companies into a central database through traditional extraction, transformation, and load (ETL) batches. However, in the last 18 months, Pfizer has turned to virtualization. The company uses data-syndication technology developed by Composite software to directly draw data sources, no longer analyzing data as it was before, and creating a virtual data view without creating a database.

One of the biggest advantages of this approach is to have the data administrator agree on the definition of the data and the source data, and then draw, test, and deploy the consolidated Data view through the abstraction layer of the composite company. Virtualized data is no longer replicated and merged, which provides a consolidated view of all the plotted data.

Pfizer's approach was validated in 2009 when the company incorporated Wyeth's research and development data into OneSource within a week of the deal's completion. Senior executives were able to see the most promising drug processes, as well as possible product overlap and synergies between the two companies. This process is much shorter than it used to be. In the 2004 acquisitions, they took months to integrate similar data, Green said.

How does it work? The answer is that through virtualization, the hardest part of the consolidation process can be completed ahead of time. Pfizer and Wyeth's teams did not share actual data until the formal end of the merger, but onesource a consensus on the exact translation of two teams in terms of definitions, reference terminology, formats, and critical phases of their drug development. "We know that one day in the merger process, Wyeth's data format will fit our data model, so we can easily integrate Wyeth's data into our existing database," Green said.

To be able to browse the data, Pfizer directly implemented a small data visualization based on Adobe Flex at the top of the OneSource. As a result, green almost no longer needs large data transformation and reporting architectures, which are often provided by business intelligence suites. This is not to say that Pfizer has completely abandoned the business intelligence suite. OneSource is only used for sharing in the research and development field. Finance, the market is still using business intelligence kits that include SAP BusinessObjects and IBM Cognos.

This approach is applied in the pharmaceutical industry to areas where speed is critical-research and development. It takes years to develop a new drug and pass the certification, and many generics are gearing up to try their hand after the patent protection period. This has forced pharmaceutical companies to seize a brief opportunity to recoup their research and development investments as quickly as possible. In the event of a delay, a drug could lose millions of of dollars in earnings.

In many industries, time is money, so flexibility and virtualization integration will be widely watched.