Big Data Ingestion and Analysis
September 05, 2019 - September 07, 2019
Thursday - Saturday
9:00 am - 5:00 pm
Early Eagle Rate:
August 22, 2019
With Social Media, Search Engines and IoT devices being a part of human life, the size of Data being stored in databases inside and outside your organizations continue to grow exponentially. Enterprises will need to harness the power of this “Big Data” in order to remain competitive and ensure that all decisions made are truly data-driven.
This is an overview course to understand the most popular tools and techniques in ingesting and analyzing Big Data. By the end of the course, you should be equipped with the basic tools to start your decision-making journey using Big Data Analysis. This 2-day program combines the theory of Big Data as well as hands-on exercise with tools such as SQL and Python.
Required Laptop Requirements: Windows or Mac with Microsoft Excel or a similar Spreadsheet software
Who should attend
This course is aimed at those who want a mid-level appreciation and practice of Big Data Manipulation and Analysis. Ideal Audience includes Data Analytics practitioners and Managers of Data Analytics Practitioners in the field of:
- Marketing and Sales
- Business Analysis or Consumer Market Knowledge
After the course, you will be able to:
- Identify value of the new way of Data Analytics vs. Traditional Statistical Approaches;
- Provide a working knowledge on current Data Manipulation Tools and Techniques using SQL; and
- Demystify and provide the context and need for Data Science and Data Scientists.
- Big Data and Big Data Ingestion
- The Value of Data Analysis
- Accessibility of Data
- Understandability of Data
- Actionability of Data
- Focus on Data Directed Decision Making
- Types of Data
- Big Data vs Small Data
- Vs of Big Data
- Choosing between the traditional Statistical Approach vs Data Analytics
- Describing the Data Flow
- Data Ingestion Definition
- Data Ingestion Methodology
- Data Manipulation using SQL Exercises
- Big Data Analytics
- Data Analytics
- Types of Data Analytics – Descriptive, Prescriptive, Predictive (Python)
- Application Samples of Data Analysis
- Visualization Options
- Demystifying Data Science
- Data Science in Practice
Mr. Charles Benedict Chan
is the General Manager of Neural Mechanics handling the company’s diverse set of Artificial Intelligence and Machine Learning based products.
He started his professional career in Globe Telecom as a Business Management Associate and eventually moved on to become a Senior Product Manager handling Value Added Services and Convergent Services for Globe Broadband. He then transferred to Singapore to work for Procter and Gamble as a Regional Assistant Brand Manager handling multi-million dollar brands such as Pantene shampoos and Joy Dishwashing. He has also experience working for smaller, struggling brands including Braun beauty and grooming, and Fairy Dishwasher Tablets.
Mr. Chan earned his Bachelor’s degree in Marketing from the University of the Philippines – Iloilo Campus.