The technological advances of the last decades have impacted our world, and the business world in particular, in fundamental ways. Massive amounts of data are being gathered and stored, from individual medical records to every single truck movement via GPS for large logistics providers. Consequent to decades of information technology deployment, organizations today have more information at hand than ever before. But in many cases the information is not being utilized to out- think the rivals. Thus, organizations are missing out on a potent competitive tool.
Moreover, ever faster computers and optimization methods have become available to transform this data into information for better decision-making. All of this makes it possible to apply advanced analytical methods to business problems that were impossible two decades ago - ranging from detailed supply chain optimization to health care applications and the service industry. Data driven decisions based on the principles of management science and operations research have always been popular in large, professionally managed corporates but have become far more pervasive with the emergence of data science and business analytics. Data science grew out an exponential growth in the availability of data that is automatically generated through digital transactions like phone calls, card swipes, electronic fund transfers, e-Commerce, social media and finally, from smart sensors that are a part of the "Internet of Things".
The ancient science of statistics has found a new life and relevance because of the availability of software tools and techniques that allow oceans of data to be churned at ease to yield the valuable butter of managerial insight that allows us to address real life situations faced by managers in areas like retail, telecom, banking, finance, insurance and operations as well as Politics also. This is the genesis of the Business Analytics.
Business analysis is the discipline of identifying business needs and determining solutions to business problems. These solutions may include improvement of business processes, accommodating/ incorporating new processes or strategic planning and policy development. The person who performs this role of identification and determination is called a Business Analyst or BA. This role has emerged with evolution of software engineering and raise of Rational Unified Process-RUP to mitigate risk in project management. Clients do not have the time to make the technical team understand how business
operations, processes, compliances and competitors work; nor does the project manager have time to make business people understand how technology worked. This position of a BA actually fills this gap, to make the project successful.
Business Analytics is about quantitative analysis and predictive modeling towards data-driven competitive strategies. Exemplars of analytics are using tools to identify their most profitable customers; offer the right price; accelerate product innovation; optimize supply chains; identifying the true drivers of financial performance etc. Organizations as diverse as HSBC, PepsiCo, Amazon, Barclay's, Capital One, Procter & Gamble, Wachovia, and the research agencies illuminate how to leverage the power of analytics. Competence in analytics along with the ability to handle big-data has become a critical skill for managers of the new age business world.
Business Analyst vs. Data Scientist
Business Analytics & Data Science lie at the intersection of three key disciplines, namely Statistics & Machine Learning, Programming and the targeted Business Domain and this program is designed to address all three in significant depth. The backbone of analytics is the theory of statistics in general and machine learning in particular and these two key areas are offered as two different areas.
The role of a Business Analyst involves researching and extracting valuable information from data sources to explain business performance (present and future). A Business Analyst also determines the right approach to improve the business. Business Analysts come with domain expertise but limited statistical abilities. This gap is filled by Data Scientists who are advanced statisticians.
A Data Scientist develops and deploys algorithms using statistical programming that support the Business Analyst's plans. A Data Scientist automates the Data Analyst's plans and models to help the business enhance output and performance.
Need for Business Analytics
Business problems need solutions based on data, not intuition. Yet most organizations struggle to translate the abundance of data they have today into meaningful business insights. Now more than ever, data analytics, approached with a business management mindset, is an essential function for successful decision making in every industry.
A Business Analyst is a hybrid IT/Business professional much in demand but scarce in availability. A Business Analyst advises organizations to follow best practices, helps in building appropriate solution strategies, provides solution assessment & validation etc. A well trained and an experienced Business Analyst is an indispensable asset to an organization. He can help frame problems, create comparisons, forecast outcomes, and make predictions. And the people who can make meaning from data in a way that stakeholders and executives can easily understand often become some of the most valued people in a company.
Skill Gap (Market Size)
There has been extensive popular interest in Business Analyst over the past few years, including popular business press books like "Competing on Analytics and Predictive Analytics." This reflects the significant business interest in translating analytics into business advantage. Employment forecasts predict a huge growth for managers who understand analytics to lead big data initiatives in the business world over the next decade.
The demand for Business analytics is huge in both domestic and international job markets. According to Newscom, India's analytics market would increase two times to INR 15000 Crores by the end of 2019. There has never been a better time to make a career into Business Analytics. This course will assist prospect interns in preparing for a career in the field of data analytics by providing you end-to-end career support, right from skill-based business analytics training to job assistance.
According to research conducted by McKinsey Global Institute - by 2018 the business universe will experience a shortage of 190,000 skilled data scientists, and 1.5 million managers and analysts capable of reaping actionable insights from the big data deluge. With an estimated 40,000 exabytes of data being collected by 2020 - up from 2700 exabytes in 2012 - the implications of this shortage become apparent.
Benefits of Business Analysis
Business Analysis is one of the most robust and in demand skill compared to the other skills, Following are the points, which make Business Analysis unique, and most sought skill among professionals.
Improving the decision making process (quality & relevance)
It is technologically independent.
Having penetration to all the business domains.
Offer better risk management and future planning to the organizations.
Have a critical role to play in global offshore delivery model.
Unlike of technical skills, it is functional in nature and does not have dynamic nature, i.e.
Whatever you learn today, it is going to help you throughout your life, but technology changes in every 6 months.
As its nature is more business related so pay and perks are always on higher side than technology jobs, provide better job security, as in case of economic slowdown the role of Business Analysis team becomes more critical.
Growth path is fastest, because nature of the job is Managerial.
Gives better job satisfaction as one is involved in core analysis concepts and out of box thinking is always appreciable in this, and whatever you learn you apply in real time.
Competence in the principles and practices of business analysis.
Participation in a recognized professional group.
Recognition of professional competence by professional peers and management.
Advanced career potential due to recognition as a professional business analysis practitioner
Apply methods, tools, and software for acquiring, managing/storing, and accessing structured and unstructured data
Prepare data for statistical analysis, perform basic exploratory and descriptive analysis, and apply statistical techniques to analyze data
Apply descriptive, predictive and prescriptive analytics to business modeling and decision-making
Demonstrate orally, and in writing, the ability to explain complex analytical models and results
Business Analytics will empower learners with the skills, insights and understanding to improve business performance using data, statistical and quantitative analysis, and explanatory and predictive modeling to help make actionable decisions.
The use of business analytics has grown exponentially in all areas, including healthcare, government, retail, e-commerce, media, manufacturing, and the service industry.
The result is an increased need for employees with an analytical approach to management who can utilize data, understand statistical and quantitative models, and are able to make better data-driven business decisions.
Career prospects include business analyst, business intelligence analyst, business development manager, market research analyst, marketing intelligence analyst, digital marketing manager, chief operating officer, strategist, and chief marketing officer.
A professional with domain knowledge (finance, healthcare, service industry, manufacturing or FMCG) can work as a Functional Business Analyst and the technical team (IT, Engineering and systems) can work as Business Analyst/ Technical Analyst / Systems Analyst.
The remuneration in this industry depends upon the organization, nature of work and the area where you work. The average starting salary of a Business Analytics in the data industry is Rs 15000 per month. Depending on various posts, the salary range varies Rs.12000 to Rs.45000 per month (min.). The special packages, bonus, incentives offered are part of this career. The remuneration outside India also varies depending upon many factors such as organization, type of analysis and places.
As opted this, interns will chart a path to analytics excellence for themself, for division and for the organization. They know how to use business analytics as a strategic advantage.
Customer analytics, also called customer data analytics, is the systematic examination of a company's customer infor-mation and customer behavior to identify, attract and retain the most profitable customers.
In this we learn what data can and can't describe about customer behavior as well as the most effective methods for collecting data and deciding what it means. Understanding of the critical difference between data which describes a causal relationship and data which describes a correlative one as you explore the synergy between data and decisions, including the principles for systematically collecting and interpreting data to make better business decisions. Interns also learn how data is used to explore a problem or question, and how to use that data to create products, marketing campaigns, and other strategies. By understanding this interns have a solid understanding of effective data collection and interpretation so that you can use the right data to make the right decision for business organization.
Once data has been collected and interpreted, what do we do with it? One will learn how to take the next step: how to use data about actions in the past to make-to-make predictions about actions in the future. Interns will examine the main tools used to predict behavior, and learn how to determine which tool is right for which decision purposes. Additionally, they will learn the language and the frameworks for making predictions of future behavior. Getting this they will be able to determine what kinds of predictions you can make to create future strategies, understand the most powerful techniques for predictive models including regression analysis, and be prepared to take full advantage of analytics to create effective data-driven business decisions.
One learns how prescriptive analytics provide recommendations for actions you can take to achieve your business goals. First, you'll explore how to ask the right questions, how to define your objectives, and how to optimize for success. You'll also examine critical examples of prescriptive models, including how quantity is impacted by price, how to maximize revenue, how to maximize profits, and how to best use online advertising i.e. social media & strategy. By the end of this module, interns may be able to define a problem, define a good objective, and explore models for optimization which take competition into account, so that you can write prescriptions for data-driven actions that create success for your company or business.
Capstone Project/ Application/ case study
How do top firms put data to work? In this interns will learn how successful businesses use data to create cutting-edge, customer-focused marketing practices. They will explore real-world examples of the five-pronged attack to apply customer analytics to marketing, starting with data collection and data exploration, moving toward building predictive models and optimization, and continuing all the way to data-driven decisions. At the end of this, they will know the best way to put data to work in business, based on the most innovative and effective data-driven practices of today's top firms.
Technology Skills: an understanding of a wide range of tools like Python, R, Spark, Excel, SQL, SAS, Hadoop, MongoDB (NOSQL), Amazon AWS (EMR / EC2), QlikView and Tableau that are commonly used to extract, analyse and visualize data.
Statistical Modeling and Analytical Skills: knowledge of statistics, data mining, machine learning and deep learning techniques and the ability to create predictive models
Applying analytics to business situations: a fair understanding of business functions like marketing, finance, operations and the application of Analytics in verticals like BFSI, retail, telecom, Healthcare etc.
Indian institutions offering Business Analytics courses
Institute Course name Course duration
SCMHRD, Mumbai MBA Business Analytics 2 years, full-time
Prin. L. N. Welingkar Institute PGDM Research and 2 years, full-time
of Management Development Business Analytics
NMIMS, School of Business Certificate Program in 1 year, part-time
Management Business Analytics
Indian School of Business- Certificate Program in 1 year, full-time
ISB Hyderabad Business Analytics
IIM- Kolkata, ISI &IIT- PGDM (Business Analytics) 2 years, full-time
Kharagpur Jointly offering
Some of the State/Private universities are also offering this program across the
country. This list is indicative only.
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