13 February 2017

BUSINESS ANALYTICS -An Overview for MU-SIGMA Job Description PDF

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BUSINESS ANALYTICS-An Overview for MU-SIGMA Campus Placement Tricks
What do you mean by Business analytics?
Business analytics (BA) refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. In contrast, business traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning, which is also based on data and statistical methods.
Business analytics makes extensive use of statistical analysis, including explanatory and predictive modelling, and fact-based management to drive decision making. It is therefore closely related to management science. Analytics may be used as input for human decisions or may drive fully automated decisions.
Types of analytics
• Decisive analytics: supports human decisions with visual analytics the user models to reflect reasoning.
• Descriptive Analytics: Gain insight from historical data with reporting, scorecards, clustering etc.
• Predictive analytics (predictive modelling using statistical and machine learning techniques)
• Prescriptive analytics recommend decisions using optimization, simulation etc.
Basic domains within analytics
• Behavioural analytics
• Cohort Analysis
• Collections analytics
• Contextual data modelling - supports the human reasoning that occurs after viewing "executive dashboards" or any other visual analytics
• Financial services analytics
• Fraud analytics
• Marketing analytics
• Pricing analytics
• Retail sales analytics
• Risk & Credit analytics
• Supply Chain analytics
• Talent analytics
• Telecommunications
• Transportation analytics

Mu Sigma is a management consulting firm that primarily offers analytics services. The firm's name is derived from the statistical terms "Mu (μ)" and "Sigma (σ)" which symbolize the mean and the standard deviation respectively of a probability distribution.
Mu Sigma is headquartered in Chicago with its main delivery centre in Bangalore. Mu Sigma's clients include more than 125 Fortune 500 companies.
Mu Sigma was founded by Dhiraj C Rajaram, a former strategy consultant for Booz Allen Hamilton and PricewaterhouseCoopers, in 2004. In 2008, Mu Sigma raised its first institutional investment round of $30 million from FTVentures (now FTV Capital)
In 2012 Mu Sigma received a bronze Stevie Award for Company of the Year in the Diversified Services category. The company was ranked #907 on the 2012 Inc. 5000 list of America's fastest-growing private companies. In 2011 the company ranked #386, and in 2010, it ranked #204.
What does it do?
It helps organizations traverse the journey from Data Engineering to Data Sciences and Decision Sciences thereby institutionalizing Decision Support.
What do you mean by Big Data? (Very important. Read the whole topic)
Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer,
visualization, and information privacy. The term often refers simply to the use of predictive analytics or other certain advanced methods to extract value from data, and seldom to a particular size of data set.
Big data analytics is the process of examining large data sets containing a variety of data types -- i.e., big data -- to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. The analytical findings can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over rival organizations and other business benefits.
The primary goal of big data analytics is to help companies make more informed business decisions by enabling data scientists, predictive modellers and other analytics professionals to analyze large volumes of transaction data, as well as other forms of data that may be untapped by conventional business intelligence (BI) programs. That could include Web server logs and Internet clickstream data, social media content and social network activity reports, text from customer emails and survey responses, mobile- phone call detail records and machine data captured by sensors connected to the Internet of Things. Some people exclusively associate big data with semi-structured and unstructured data of that sort, but consulting firms like Gartner Inc. and Forrester Research Inc. also consider transactions and other structured data to be valid components of big data analytics applications.
Big data can be analyzed with the software tools commonly used as part of advanced analytics disciplines such as predictive analytics, data mining, text analytics and statistical analysis. Mainstream BI software and data visualization tools can also play a role in the analysis process. But the semi-structured and unstructured data may not fit well in traditional data warehouses based on relational databases. Furthermore, data warehouses may not be able to handle the processing demands posed by sets of big data that need to be updated frequently or even continually -- for example, real-time data on the performance of mobile applications or of oil and gas pipelines. As a result, many organizations looking to collect, process and analyze big data have turned to a newer class of technologies that includes Hadoop and related tools such as YARN, MapReduce, Spark, Hive and Pig as well as NoSQL databases. Those technologies form the core of an open source software framework that supports the processing of large and diverse data sets across clustered systems.
Clients of Mu-Sigma
• Microsoft
• American Public Corporation
• Pfizer
• Dell
• Ten US Commercial Banks

Mu Sigma is a leading provider of decision sciences and analytics solutions, helping companies institutionalize data-driven decision making. Being an ISO 27001 certified company; they are committed to information security at every level.
Mu Sigma fragments into Information Modelling, Domain specific analytics & technology development.
The horizontals spread of Mu Sigma is Risk, Marketing & Supply Chain whereas vertically they are aligned to Financial Services, CPG/Retail/Technology, Pharmaceuticals.
Mu Sigma’s proprietary assets includes products like MRx, MMX, MRIP, in addition to this they also have expertise resource in SAS/R usage.
Mu Sigma clients list includes Microsoft, Dell, leading retail companies, etc.
The company also has a dedicated Innovation & development group catering new technologies, models and applications so as to come up with new solutions better equipped to client’s needs.
-Prepared By
Souvik Majumder Campus Placement Tricks

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