Big Data & Business Analytics

Big Data Analytics


Why Business Analytics

1. The future – Industry have so much of data available now generated during the digitization phase in last 2 decades. Now is the time to utilize this data for executive management and strategic decision making.

2.Biggies like Tesco, Wal-mart, American Express, New York Stock Exchange etc have already Big Data implementation on the way.

3. McKinsey Global Institute’s Big data: The next frontier for innovation, competition, and productivity estimates that by 2018, “the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know- how to use the analysis of big data to make effective decisions.

4. 90% of fortune 500 companies will have big data initiatives underway by end 2015.

Benefits of Big Data Analytics Course

1. Analytics using Big Data can be leveraged across all industries including Pharma, Telecom, Manufacturing, Retail, Health care, Public Sector Administration.Big Data & Business Analytics

2. Estimate of over 2.5 lakh big data analytics jobs to be in there by mid 2015 in India alone.

3. Learn from the experts – We have engaged the best brains in the industry with a sea of practical and implementation experience in the field to give you the best available knowledge and share the real life case studies and experiences across different domains to prepare you for the real world.

4. Learn and understand the applicability of Big Data analytics using cross section of tools and technologies that can be used tomorrow.

Course Contents

Module 1 : Basics of Business Analytics & Business Mathematics

Module 2 : Predictive Analytics and Advanced Techniques

Module 3 : Business problem solving using advance analytics

Module 4 : Analytics in the age of Big Data

Module 5 : Big Data implementation across domains

Module 6 :Big Data Architecture

Module 7 : Data management using big data

Module 8:Benefits and business implementation of big data over the conventional

data management

Swift technological prowess in fields such as robotics, data sciences, artificial intelligence and business analytics are fueling in new work opportunities, while reshaping the existing ones. These technologies themselves are not static and continue to evolve. This has massive implications for the larger economy.Opportunities are available now, but soon we will witness the next wave. Businesses are also looking at different approaches at data warehousing so that a lot of irrelevant information may be filtered out. Only that data is useful which will provide strategic insights. Deriving these insights is also an art, not just a scientific puzzle. Due to the dependence on data, legacy firms’ assets are getting underutilized. The extent of digitization varies unevenly across industries. McKinsey has even formulated a Digital Quotient Score to gauge the score lines for different companies. 84 was considered a high, and lowest was 4, with 34 out of 100 being bang average. Emerging economies are still well behind the developed ones in terms of leveraging its digital potential. Leaders amidst this situation must constantly experiment, learn and scale up fast. Existing business models need to be remodeled. The balance sheet now needs to incorporate intangible digital capabilities too. Humans and machines need to be aligned so they can work together.


Uploaded Date:23 June 2018

Companies have been experimenting with different ways to use and get benefitted from business analytics. As per an estimate by the McKinsey Global Institute, it can generate business global of between nine and fifteen trillion US dollars. Yet, many companies are not satisfied, claiming that this use of analytics is not giving them the right sort of business intelligence to base their decision-making on. So, McKinsey did a study spanning twelve different geographies for companies with total revenues in excess of a billion. Some leaders have indeed cracked the code of using analytics at scale. One of the key areas in which these leaders break away from the rest is that their entire strategy is aligned towards the analytics data. This data to be captured and further sieved through requires the right foundations in terms of both people and technologies available. Collaborative, cross-functional teams need to be put in place. The front-line staff needs to be empowered to make use of the data emanating. This helps analytics bridge the gap with the last-mile.


Uploaded Date:23 June 2018

Infrastructure developers are amongst the most asset-rich owners. They also generate enormous data during the project planning phase but are amongst the laggards when it comes to the use of business analytics. They are way behind industries such as retail, automotive and financial services. That is why their decision-making is too often qualitative rather than based on hard evidence. In order to embrace this technique towards a predictive system, infra companies must adopt a three-phase approach. It starts with design and data ingestion, followed by the proof of concept and then scaling. At the first phase, an exploratory analysis must be done. For this the data warehousing has to be done, as otherwise it will not be in the organized form the company would want. Only then will it be able to perform complex tasks such as correlation, natural-language processing, signal processing, outlier removal and data merge. At the next, algorithms need to be finalized and models validated. Now regression, clustering and network analysis will be possible. Permutation and holdout tests need to be performed. Before the final phase, an initial pilot has to be geared up. To close it proper scaling must be defined as the aims. The company must also ensure regular model maintenance.


Uploaded Date:23 June 2018

Simply having truckloads of big data does not always equate to having the right kind of information. While a decade back, only the most forward-thinking and innovative companies were using data-backed business analytics, but now it is everywhere working on the who, what and where of customers. One of the earliest ventures still surviving is the Wharton Customer Analytics Initiative (WCAI) which recently completed its decade working. It started off with analyzing customer data in the music industry for Napster. The WCAI soon realized that the bigger slice of the bucks would come emanate from media and not entertainment, so the focus was adopted accordingly. A few years further on, digital advertising would get added on as the latest buzzword along with interactive media. The industry has evolved to have more internal teams, rather than any dependence on external agencies. Data has now become much more diverse so greater sophistication is needed to glean the right kind of information. There is now increased collaboration between marketing, research and the CFO’s teams. There has also emerged a subtle difference between the terms beginning with data- analyst, engineer and scientist. Going ahead, a greater amount of care will need to be taken by all agencies involved with data, due to the negative press arriving from recent violations of privacy norms.


Uploaded Date:22 June 2018

Several companies are now in the business of data warehousing. Enormous amounts of personal and official data is stored but not all zealously guard the information. Some companies have faced public backlash for their lack of proper data protection. According to a study by BCG, this data can churn revenues worth more than a trillion US dollars by 2020. This is because this data gets used in the business analytics process to unlock insights about customer use or preferences. But misuse can also render this data as dangerous. A lot of complex legal documents are written by companies so that consumers end up signing up for use of their data. Even those that are ethical end up stressing out their customers due to privacy breach issues. BCG advocates for misuse of data to be punished more strictly than a mere breach.


Uploaded Date:19 June 2018

Vineyard Vines was started by the Murray brothers who wanted to do something of their own, and not be tied to regular jobs. Its pink whale logo is now widely identifiable in the USA, with over ninety physical stores and similar success on e-commerce. However, the marketing technique is evolving. Over the years, the company has captured copious amounts of data on customer usage patterns. The data warehousing at Vineyard Vines runs into the terabytes. This has provided vital insights on business, enabling the marketers in the company to plan its campaigns more precisely. The digital marketing and communication that is driven by Vineyard Vines is now authentic, targeted and relevant. One of the key interventions this data-driven analysis and communication ahs done is to notify customers about stock replenishment during high demand-times. Last-chance offers are communicated for out-of-stock items. Special event and holiday-specific campaigns are run. There is also proactive identification of customers who may soon unsubscribe.


Uploaded Date:14 June 2018

Amazon already holds two-fifths of the online marketplace, but is growing at such a pace, that it will soon by 2021 cover half of it. But the Seattle-based e-commerce giant’s footprint does not stop there, as it has successfully expanded into several other businesses in recent years such as Cloud services, media, B2B distribution and hardware. This vast ecosystem means that Amazon ahs now become central to any due diligence effort made by Private Equity (PE) funds. The Amazon Factor as it is known also translates to a humungous quantity of data warehousing which allows for superior decision making. Such readily available data may be then used by PE funds for performing due diligence operations. According to a study by Bain, Amazon has the highest Net Promoter Score among top retailers across categories. The data advantage that Amazon provides also allows for detailed business analytics operations to be conducted. Future penetration can best be predicted using this as it tracks pricing, convenience to customers and return policies. For those doing due diligence tests, knowledge in each category is vital.


Uploaded Date:13 June 2018

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