TOP 5 REASONS TO ATTEND THIS MASTERCLASS
* UNDERSTAND clearly what Big Data, Data Science, Big Data Analytics and Role of Visualization is
* GAIN full understanding of the simple 7-step process that you can apply to complex problems in YOUR domain
* LEARN various tools and techniques available for Big Data Analysis
* BE ABLE to use simple tools and technologies to go through the complete Big Data Analytics value chain
* HAVE THE ABILITY to speak about Big Data Analytics and Data Science, across their own and other organizations
WHO SHOULD ATTEND?
* The workshop is primarily meant for people engaged with all aspects of Data and communicating their data, findings and analysis
* CIOs, CTOs from domains such as Retail, Oil & Gas, E-commerce, Pharma, FMCG, Telecom, IT, Business and Management Consulting, Corporate Analysis and Advisories
* Marketing, Finance and Sales Managers and Executives
* Business Leaders who work with large quantities of data
* Business Analysts & Reporting Professionals
* Professionals with strong interest in Data Analytics and getting insights from their data
What is Big Data? Is it just Hype?
Big Data is no longer hype. It is in fact akin to the next Industrial Revolution. If you are not using Big Data and Data Science in your business sector, be assured that your competitors are - if not today than surely tomorrow.
Be two steps ahead of them.
Today Big Data has moved beyond the hype and can empower you to take data based decisions in your business. Gut feel was fine in earlier days, when data was insufficient. Even today, gut feel is great, but if backed by data - it can be a winner in almost any sector that you can think of.
Big Data does not mean just a large volume of data, it is much more than that.
Who is using Big Data?
Well, who isn’t?
Companies in a wide spectrum of sectors like Ecommerce, Retail, Oil & Gas, Manufacturing, Distribution and Logistics, Banking and Financial Markets, Automotive, Telecom, Pharmaceuticals, Medicine and Healthcare, Biotech and Cybersecurity are taking advantage of Big Data to grow their businesses, focus their efforts and derive value.
Big Data means that we can create models of the world more easily and also test them out, to spot correlations, trends and behaviour that until now was difficult to do with a high degree of confidence. However, the traditional techniques of data analysis and number crunching no longer work in todays big data world. When you have petabytes of data to be modelled and analysed, you do need a different set of principles, techniques and methods to gain valuable insights from all this data.
You simply cannot use traditional tools and software to meaningfully get insights from such data.
Why is Big Data being talked about now? Data was always there?
Yes and No. Data was always there, but often not enough and in a hard to manipulate form, trapped in various islands like filing cabinets, registers, forms, paper files and documents. Today we have a data explosion, that too, in a digital form that can be easily stored, retrieved and analysed. In the year 2014 we arrived at a point where the data available in that year was more than all the CUMULATIVE amount of data available until the year before that. This is exponential growth.
The explosion of mobile and connected devices has led to a situation that we have enough data to analyse and predict the performance of business models to a far more accurate level than it ever was.
Why this Masterclass?
This is not just another “Hadoop training” course (Hadoop will be covered, but as a part of the full spectrum of tools available to work with Big Data). There are enough courses, books and materials out there, that train people in the nuts and bolts of handling Big Data at a machine level. What you should be looking out for, as a business leader or manager, is
a) Understand what technologies are available in the Big Data space
b) How to derive value from the data that is already available in your organization
c) Learn how your own industry sector as well as other sectors are deriving value from their own Big Data Projects
Mere access to Big Data does not imply that it can be easily used. The old data crunching methods cannot be used efficiently and effectively with these large quantities of data. You need to know and use the proper techniques to analyse the data, build models and gain insights into how your business can prosper.
Do you know the 4 enablers of Big Data? While most people talk about 3V's or 4V's of Big Data, in this Masterclass, you will learn about the 7 pillars of Big Data and have a clear understanding of Big Data.
* Also, you will Understand what is emerging Big Data Stack?
* Understand the framework for Big Data for creating value?
* Be introduced to various technologies that allow to you create value from Big Data
* Learn about need for data science and learn about Data Science.
* Learn how various industries are leveraging Big Data, their successes and failures
What will this Masterclass cover?
* Data Science Overview
* Big Data Technologies– HADOOP and related applications
* Big Data Analytics
* Big Data Visualization
* Use Cases from different sectors such as Ecommerce/ Retail, Healthcare/ Insurance, Oil & Gas
* Your own Use Case? (Bring your own)
MASTERCLASS DETAILED CONTENTS
Here's what you will learn in the Masterclass in detail.
Data Science Overview
Data Science is one of the key components for creating value from Big Data. Using data science one can create meaningful, actionable insights from small to large data, simple to complex data and static to streaming data, from smart data to dark data. Data science is practiced by folks known as Data Scientists in the industry. A talent hard to find world-wide. There are very few true data scientists? Are you one of them? We will learn answers to these question. Also, you will
* Learn where data science fits in the analytics value chain of an organization.
* Understand why one needs to go beyond business intelligence
* Get introduced to various tools and technologies e.g. R, Weka, SciPy, Python, etc.
* Understand how to think like a data scientist.
Big Data Technologies Hadoop and related applications
One of the key enablers for creating value from Big Data is modern data management technology. The most popular one is called Hadoop. Do you know why it's called Hadoop?
Hadoop enables to store, process wide variety of data, large or small and provides scalability and ease of managing data are different scales and takes
it beyond the limitations of traditional data platforms. In this course you will be introduced to various technical terms like HDFS, Hive, Pig, MapReduce, Spark, Hbase, etc. You will see the role of distributed/parallel processing and we will discuss use cases where it becomes important.
Big Data Analytics
In this part of the Masterclass, we will briefly present how one installs some of the data science tools. A sample of data sets will be use to discuss the 1st enabler of Big Data - i.e. Data. What different data types exists. How data science tools empowers one to make sense out of such data sets. A brief introduction to evolution of analytics will be discussed. Also, a brief introduction to machine learning and artificial intelligence will be provided. Then, you will
* Learn how to look at data ( you will be provided data sets ) with different tools of data science
* Learn to build predictive models and learn to interpret the results
* Get a flavor of some statistical analysis and machine learning algorithms
* Understand the terms like training, testing data
* Understand what predictive modeling means and role of visualization, which will covered in next session
Big Data Visualization
All organizations have lot of data sitting in their silos. Business intelligence is used to generate answers to the questions one already knows. In Big Data revolution, one needs to create new patterns by mining and connecting disparate data sets using Big Data Analytics and Big Data Technologies. The patterns are recognized and interpreted through what now one calls Big Data visualizations. These visualizations can be simple heat map to a complex set of sweet spot 3-dimensional
surface maps of objects. Just doing Big Data Analytics is not enough, one needs to learn to tell a story from the Big Data visuals that are results of the analytics and ask the questions from the new patterns. We will discuss all these topics and also Big Data Visualization
* Create and generate different visualizations from different tools like R, Weka, RapidMiner, Tableau, etc.
* Discuss how each of us interpret what we see?
* Understand the concept of visual analytics
* Understand the difference between the different levels of visualizations needed across the enterprise
* Explain the role of operational charts versus business executive visuals
This Masterclass will cover practical use cases from different industry and business sectors. These use cases help you learn how you can apply what you learn in the Masterclass to your own business or industry. We will cover three Use Cases. What's more, you can get your own Use Case (if you have a problem that could be solved with Big Data techniques and you are willing to share it with the participants, you can get it to the Masterclass).
USE CASE 1 (E-Commerce / Retail)
A large number of companies are facing many threats from cyber attacks. If you are ecommerce company, then one of the threat is distributed denial of service (DDos) attacks. In this case study, you will learn how to build predictive models using big data and data science. A step by step method will be described to you, for data discovery, problem and approach to the solution.
USE CASE 2 (Healthcare / Insurance)
Given the fast pace of health care industry expansion in India and USA. Can you find easily which hospitals have a better track record in terms of treating certain disease? Do some hosptials or doctors have higher rate of patient return within certain days of a procedure performed? Can Big Data and Data Science help? In this case study analysis using open source R will be discussed.
USE CASE 3 ( Oil & Gas)
Oil and Gas industry have a significant amount of dark data. However, the industry has been using machine learning algorithms for a long time, but the value creation from it has not helped the industry. In this case study, we will discuss some challenges and solutions to solving some of the complex problems in the industry. Within the country context, some of the top companies have highest failure rates during the drilling phase of oil well, much more then their industry peers in other countries. We will discuss some of the approaches that one can take by leveraging big data.
Contact us at sales[at]abhisam.com OR call us on +91 22 21732956 for more info.