Discuss about the Business Intelligence.
This report is based on concept of business intelligence. BI is considered as a term that talk about variety of software applications that are required to use evaluation of organizational raw data. There are several related activities that build business intelligence such as data mining, reporting, online analytical processing and querying. Now in this report, we will emphasize on different topics related to business intelligence. These topics will help to understand important and usage of business intelligence.
In this segment of report we will analyze three different articles related to business intelligence.
Article-1: Synergy hones agile delivery with BI
According to provided information in this article, Synergy is a Western Australian energy provider and it is using business intelligence and digital projects to improve capabilities of agile delivery. It will be done under CIO of Synergy. According to CIO, they are implementing two main programs to benefit from the agile drive. The first program is related to business intelligence stream of work to add value to the implementation of SAP HANA and another program is regarding digital stream to improve the way of interaction of customers with Synergy online. According to CIO of Synergy, agile methodology is a real journey for them and they are focusing on driving projects, products and services via the web by using agile methodology (Technet.microsoft.com, 2017).
From analysis of business intelligence, we found four major capabilities of it that have potential to make BI effort work together. In next segment we will discuss that how these capabilities are helpful to make effort of BI together. The four synergistic capabilities of business intelligence are listed as below (Crozier and Crozier, 2017):
- Organizational Memory
- Information Integration
- Insight Creation
- Presentation Capability
This capability of business intelligence is related to the information storage and knowledge in easier to access form. Historical information and explicit knowledge accumulated over time in case of organizational memory. There are some factors that are necessary for organizational memory capability and those factors are technological progress, extensiveness of computers for creating and improving documents, presentations, to enhance use of emails, social media, and improvements in knowledge management technologies. This Business Intelligence capability is useful to make the BI effort work together in a way that it is associated with the ability of searching large enterprise content across multiple different databases. Other three capabilities depend on this BI capability directly and indirectly, because these capabilities can use knowledge over time, real-time content for decision making and for creating insights (Google Books, 2017).
This business intelligence capability is used to link past structured and unstructured data from different sources of information. As we know that, first capability of BI i.e. Organizational Memory is connected with past information. Therefore, Information Integration capability depends on Organizational Memory. In this linking process of data, some essential factors are included by information integration capability such as knowledge and structured information from ERP, systems related to transactions and knowledge sources, external knowledge and information from web mining and environmental scanning and unstructured knowledge and information from text mining and digital content management systems (SelectHub, 2017). This business intelligence capability is highly preferred to produce content from different sources that can be used further to produce insights which is next capability of BI. In this way, Information Integration capability also shows its togetherness with other BI capabilities and from this it is cleared that BI effort work together.
Insight creation is facilitated by Information Integration capability and Organizational Memory to create insight creations by providing integrated data, information and knowledge that establish the raw materials required for long-term and short term decision making and insight. Insight Creation Capability provides three kinds of outputs that is description of what happened, an understanding of what happened and a prediction regarding future behavior. For Example, the creation of insights can be used for BI efforts by an organization to identify the answers for questions like “What supplementary products could be vending to our customers?”
and “Which customers company is most likely to lose?”. The input of insight creation capability is further used in next BI capability that is presentation capability.
This BI capability is used for appropriate reporting and balanced scoreboard tools, so that Business Intelligence can become more valuable to its users. Presentation capability is actually point of contact between BI solution and its user. This BI capability is focused on convenient features of the BI solution that include presentation of results in a customized and user-friendly form. For example: An airlines company has made excellent use of presentation capability of BI by using an effective Flight Management Dashboard. This interactive graphical user interface, together enable the operational staff to detect issues in network of flights and also manage flights accordingly to enhance customer satisfaction. It is a best use of BI efforts by Airline Company.
On the behalf of above discussion, we can say that BI capabilities work together in above ways to make BI effort work together.
Article-2: “Netflix Purposely Designed ‘House of Cards’ to be a Major Hit—Here’s How They Did It”
On the behalf of above article, we will discuss that how Netflix was able to get it right but not Amazon for a TV show? There is no doubt that behind our TV shows, efforts of creative geniuses contribute a lot. But is it possible to attribute some of their popularities to data analysis as well? According to Munich based data scientist Wernicke said that optimum results are not always produce by data analysis. To prove this, Netflix and Amazon are served as examples here. Here are two shows which were made strategically with data analysis methods. One show worked on Netflix’s House of Card and went on to score of 9.1 on rating curve. Another show worked on Amazon’s Alpha House and fell short and went on score of 7.5 on the rating curve. It was considered an average show. Both companies are competitive data-savvy companies and connecting millions of data points. But one company did well and another did not (Mazenko, 2017). Why it happened? Eventually, when Amazon set out for making data driven show then it held a competition. By Amazon, a number of ideas of shows were analyzed and eight of them were selected (OLAP.com, 2017). After doing all these things, an experimental episode created for each and also made available online free of cost. The episode was watched by millions of people and data regarding total number of viewers of this episode, how long this episode watched by them and which parts skipped by viewers, used by Amazon to create a show (SearchDataManagement, 2017).
On another side, at same time Netflix was preparing something similar. But the difference here is instead of using a competition, Netflix viewed other platforms such as ratings, viewing history etc. This data was further used to discover small bits that what is actually liked by users. This was the main reason that show was successful on Netflix’s House of Cards, not on Amazon’s Alpha House. On this, Mr. Wernicke gave explanation that Amazon’s show was not successful because they used data all the way. But Netflix concentrated on point that what users like the most and used that insight to think about a concept. That is why Netflix’s show was a big hit. Here Insight Creation capability of Business Intelligence helps a lot of Netflix (Fda.gov, 2017).
Article 3: Six Ways big Data is Driving Personalized Medicine Revolution
In this segment we will emphasize on an essential question that how Business Intelligence can integrate safe clinical and personalized medicine to all stakeholders. As we know in field of medicine, drugs are expensive, difficult to research and hard to get approved. According to a report, it is found that most of drugs do not work on large parts of the population. In these case, pharmaceutical companies have pressure to research drugs that can be effective for people and must have highest probability of turning profit. But this can be done by IT and Big Data. Both technologies are putting major impacts on the way of researching drugs by creating more effective trails (InformationWeek, 2017). In the journal Nature represents that 10-highest best prescribing drugs in U.S work on only one patient among four. Multiple reasons are provided by Nature Journal, but the main reason is that, different genetic makeups, proteins in our body and body flora effect on working of drugs. After knowing about these issues, drug companies are trying to address these criticism and try to make more accurate drugs. In this case business intelligence can also help in following ways (SearchBusinessAnalytics, 2017):
- Through BI, analytical modeling of biological processes is possible and through this drugs can become more sophisticated and widespread. Analytical modeling can help to identify new potential candidate fragments that has highest probability to being successful in development of drugs (Lazzaro, 2017).
- To identify safety or operational signals that are required to neglect important issues of unnecessary delays and argumentative events, the trials of medicine can be monitored in real time. (McKinsey & Company, 2017).
- With the help of Big Data as BI application, the way of trails of designing and administrating treatments are changing. By using Big Data, correct and modified medicines are introduced to drug trails and research that reduces cost and improve outcomes.In this way BI can be used to integrate safe clinical medicines.
Crozier, R. and Crozier, R. (2017). Synergy hones agile delivery with BI, digital projects. [online] iTnews. Available at: https://www.itnews.com.au/news/synergy-hones-agile-delivery-with-bi-digital-projects-421297 [Accessed 12 Apr. 2017].
Technet.microsoft.com. (2017). Business Intelligence: Planning Your First Microsoft BI Solution | TechNet Magazine. [online] Available at: https://technet.microsoft.com/en-us/library/gg413261.aspx [Accessed 12 Apr. 2017].
Mazenko, E. (2017). Tableau Software Review. [online] Better Buys. Available at: https://www.betterbuys.com/bi/reviews/tableau-business-intelligence/ [Accessed 12 Apr. 2017].
SearchBusinessAnalytics. (2017). Collaborative business intelligence brings users together on BI. [online] Available at: https://searchbusinessanalytics.techtarget.com/feature/Collaborative-business-intelligence-brings-users-together-on-BI [Accessed 12 Apr. 2017].
Google Books. (2017). Business Intelligence. [online] Available at: https://books.google.co.in/books?id=T-JvPdEcm0oC&pg=PA46&lpg=PA46&dq=how+four+bi+capabilities+work+together+to+make+BI+effort+work+together&source=bl&ots=Z3zzZt2SUV&sig=TtvETNhoBwm_Q1Pma2epobT4fYw&hl=en&sa=X&ved=0ahUKEwjVsf6htp7TAhUFpo8KHWiuDDgQ6AEIHzAB#v=onepage&q=BI%20effort%20work%20togther&f=false [Accessed 12 Apr. 2017].
SelectHub. (2017). BI Capabilities List | Business Intelligence Capabilities. [online] Available at: https://selecthub.com/business-intelligence/list-bi-capabilities/ [Accessed 12 Apr. 2017].
SearchDataManagement. (2017). What is business intelligence (BI)? - Definition from WhatIs.com. [online] Available at: https://searchdatamanagement.techtarget.com/definition/business-intelligence [Accessed 12 Apr. 2017].
OLAP.com. (2017). What is Business Intelligence? BI Definition. [online] Available at: https://olap.com/learn-bi-olap/olap-bi-definitions/business-intelligence/ [Accessed 12 Apr. 2017].
Lazzaro, S. (2017). Netflix Purposely Designed ‘House of Cards’ to Be a Major Hit—Here’s How They Did It. [online] Observer. Available at: https://observer.com/2016/01/can-we-use-big-data-to-create-hit-tv-shows-as-addictive-as-breaking-bad/ [Accessed 12 Apr. 2017].
McKinsey & Company. (2017). How big data can revolutionize pharmaceutical R&D. [online] Available at: https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/how-big-data-can-revolutionize-pharmaceutical-r-and-d [Accessed 12 Apr. 2017].
Fda.gov. (2017). Drug Safety Priorities 2016: Initiatives and Innovation. [online] Available at: https://www.fda.gov/Drugs/DrugSafety/ucm522941.htm [Accessed 12 Apr. 2017].
InformationWeek. (2017). 6 Ways Big Data Is Driving Personalized Medicine Revolution - InformationWeek. [online] Available at: https://www.informationweek.com/healthcare/analytics/6-ways-big-data-is-driving-personalizedmedicine-revolution/d/d-id/1322755 [Accessed 12 Apr. 2017].