Transcript of "USING DATA AS A HEDGE AGAINST UNCERTAIN ENVIRONMENT"
USING DATA AS A HEDGE AGAINST UNCERTAIN ENVIRONMENTDATAThe amount of data everywhere is increasing. • According to THE ECONOMIST the world created 150 Exabyte’s (billion gigabytes) of data in 2005 and it is estimated to create 1200 Exabyte’s in 2011. • According to CISCO the amount of traffic over the internet will reach 667 Exabyte’s in 2013. • According to ABERDEEN’S RESEARCH an average company experience a 41% increase in data volume year on year.SO WHAT?Immediately the question will arise what we are going to do with this huge pile of data? Withthe modern technology and scientific tools we can do things which we couldn’t have imaginedyears before. GRAPH SHOWING DATA EXPLOSION IN RECENT YEARSDATA TO INFORMATIONWe can use the data to find patterns, useful information and in turn that can be used to identifybusiness trends, prevent diseases, combat crimes, etc…Gathering all the data manually and trying to find the patterns and information is a tiresome andtime consuming process. With the rising inflation and in turn increasing interest rates,depreciating rupee, American debt crisis, euro zone crisis clearly shows us that uncertaintybecomes the new normal. The organization who can grab cues immediately from global andlocal scenarios and swiftly take decision will stand out from the rest.
The other reasons are increasing pressure to raise profits, do more with less and operate moreefficiently. But we have many practical challenges. Some of them are lack of timely information,inaccurate or inconsistent data, over dependence on silo spreadsheets, tight budgets andincreasing pressure to comply with regulatory requirements.BUSINESS INTELLIGENCE AND BUSINESS ANALYTICSThe panacea comes in the form of Business Intelligence [BI] and Business Analytics [BA].Business Analytics is a part of the BI but it is often used interchangeably. Analytics can bedivided into two, descriptive analytics and predictive analytics. Descriptive analytics describeswhat happened in the past and predictive analytics predicts what is going to happen in the future.The predictive analysis is the one which can provide competitive advantage to the organizationin the form of forecasting, predictive modeling, simulation and experimental design. WHAT BUSINESS INTELLIGENCE CAN ANSWERBI includes data collection, data integration, analytics, and reporting. • Data collection and data integration includes data connectivity, data quality, ETL [Extract, Transform, and Load], data migration, data synchronization, data federation, and master data management. • Analytics includes applying statistical tools and algorithms, data and text mining, forecasting, econometrics, quality improvement and optimization. • Reporting includes dashboards and interactive graphics.
SAS BI DASHBOARDUsing BI, every data [newspaper reports, information on blogs, information on social networkingwebsites, photos, videos, internal emails, internal reports, even phone calls, boardroomrecordings] which can be digitized and analyzed can help us to find the hidden truth, which canbe a vital information for decision making.Taking business decisions based on information from data rather than ‘gut instinct’ will lowerthe risk and help the organization to be more proactive in the decision making.BUSINESS INTELLIGENCE MARKET SCENARIOAccording to Gartner during 2009 the overall IT spending was negative but Business Intelligencemarket managed to grow 4.2% and that went up to 13.4% in 2010. SAP is the undisputed leaderin BI with 23% market share followed by ORACLE, SAS, IBM, and MICROSOFT. The totalrevenue from Business Intelligence was more than $10.5 billion in 2010. There is also BI opensource vendors like Jaspersoft, Pentaho, and Actuate BIRT who are worth giving a try.RISK AVERSION COMES WITH A RISKThe present business environment becomes very competitive, commoditized, heavily regulated,and facing tough macroeconomic challenges. Business Intelligence converts the data intoinformation which is highly visible and meaningful to the organization. It helps to provide theright information to the right people at the right time. But, we cannot forget the complicatedmathematical models and algorithms which was fed with large amount of data, didn’t reflect therisk involved and led to the worst financial crisis since 1929. So increasing dependence ontechnology should be combined with rational thinking.