Business Intelligence Key Factors - How to successfully help decision making in the age of Big Data


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  • Today’s presentation will relate about the key factors of Business Intelligence, and how BI contributes to decision making within an organization, taking into account we are in the age of Big Data.You can easily get bored while listening to this subject, but once you get what it is about and understand you are surrounded by Business Intelligence every day, you will enjoy it as you will see an infinite number of application possibilities.
  • First of all, what is Business Intelligence?Business Intelligence is a vast topic. It is often called an “umbrella term” because it covers many areas. We cannot say it is only a piece of software. We cannot either say it is only a procedure to follow. It is a set of theories, processes, technologies which transform the raw data into useful information with the final goal of supporting the decision making processBusiness Intelligence solutions are part of the software industry
  • I previously said we are in the age of Big Data. Big data is a technology which appeared with the increasing data volume we are generating every second. Big Data solutions are used to process information which cannot be analyzed with the traditional processes and tools.Big Data is advanced analytics at extreme scale.IBM characterizes Big Data with the 3V: Variety, Velocity and Volume.
  • When it comes to decision making, there are several level of insight we can use.This graph is a perfect illustration of the different layers of Business Intelligence.Higher we go on the axis, more the insight received is valuable and will help the manager take better decisions.
  • What are the key factors of Business Intelligence from a customer’s point o view? What do potential customers expect from a BI system?It is important to identify what is critical to a business in order to Throughout my research several key factors came out as the most important. The query SPEED is of major importance. Many businesses analyze their data but the processing time is considerable, especially because it is done manually. They need fast results! If they need to wait more than 1 or 2 minutes for their report to be generated, that’s too much. And when they need to interact with the data, the expected waiting time is lowered to seconds.A BI system need to be VERSATILE, meaning it needs to adapt to all kind of data sources: SQL databases, Excel files, Bloomberg web services or text files.In the meantime, fresh data is required. The customers want to use their live data instead of last week’s. That’s the AVAILABILITY.COLLABORATION is a recent trend. Thanks to all our mobile devices, we can keep in touch with people from anywhere. Business Intelligence users need to share with each other the results of their analysis. Their different personal insight on each issue will lead to better decisions taken.Companies need to follow COMPLIANCE rules and a Business Intelligence system should be able to alert the user if they are not followed. Another basic but important feature in most of the software available is the SECURITY. Who can see and access the data or who can modify it?Last and most important are the VISUALIZATION tools a Business Intelligence can provide! This factor is the most important because visualizations will influence the decision in the end. The manager will look at his dashboard which shows the key indicators of the company and will take a decision based on that. On top of checking the dashboard every morning, the manager wants to INTERACT with these results, zoom-in the results and find out what skewes the numbers in the wrong way.
  • The hypothesis of this research can be stated as follows: Identifying the limitations of Business Intelligence systems to fulfill the gap between the supply and demand in the Big Data era.
  • The limitations of Business Intelligence have remained the same through the years, only at a larger scale. The challenges BI vendors need to overcome have increased, but remained proportional with the volume of data.The first step to overcome is the perceptions an executive could have on technology. Especially older-fashioned managers would better trust their gut than some numbers shown to him. They also would think BI is too complex, that they would need to hire high skilled experts which cost a lot and in the end they won’t be able to understand where the results come from. The results need to be translated into business terms and train managers to perform analysis by themselves.Cost is not only a perception, but a reality. Business Intelligence solutions are very costly to be implemented. Fortunately, there are also solutions for small businesses, but which would also offer limited possibilities and features. Businesses have a budget, in the end it will be the critical factor in the decision making process.The data movement is an issue due to the data scalability – data volume.
  • We found out there are BI limitations at the executive level blocking its implementation, along with data limitations due to the volume generated.The future of Business Intelligence stands in its ability to adapt to the new trends in technology and consumer behavior.
  • Business Intelligence Key Factors - How to successfully help decision making in the age of Big Data

    1. 1. Business IntelligenceKey Factors:How to successfully help decision makingin the age of Big Data©2013 Cristian Golban
    2. 2. What is Business Intelligence?“Business Intelligence (BI) is a set of theories,methodologies, processes, architectures, andtechnologies that transform raw data intomeaningful and useful information for businesspurposes.“ (Olivia Parr Rud)
    3. 3. Big Data characteristics
    4. 4. Insight layers of BI
    5. 5. Data Flow in a BI system
    6. 6. Speed Versatility AvailabilityCollaboration Compliance SecurityInteractivity VisualizationBI Key Factors
    7. 7. HypothesisIdentifying the limitations of BusinessIntelligence systems to fulfill the gapbetween the supply and demand in theBig Data era.
    8. 8. Limitations Executive Perceptions Costs Data Movement Data Scalability
    9. 9. Conclusions and FutureTrends Limitations in BI implementation Data volume explodes Cloud computing / SaaS Mobile BI / Collaboration Data visualization Predictive analytics