Business Analytics & Big Data

“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”

– By Geoffrey Moore, an American Management Consultant and Author

What is Big Data?

After years of computer-based record keeping, organizations now have access to massive amounts of data, this data has the potential to provide extensive insights if analyzed effectively. These massive amounts of data gave rise to the term Big Data. Big Data has a major impact on businesses worldwide, with applications in almost all industries including financial services, logistics, and healthcare. Organizations need to utilize their data and process it through analytics to make effective business decisions.

Discover Big Data with Tadafur

Tadafur has designed this course to equip you with an understanding of how big data can drive organizational change and the key challenges organizations face when trying to analyze massive data sets.

We will start the course with a historical view of Big Data, how it emerged, and its connection to Data Mining and Data Science. You will learn of potential data sources that can be used for solving business problems, and get an overview of data mining, Big Data technologies, and the relevant tools.

Our course will provide you with insights on how to identify Big Data projects in your organization, which technology platforms to use, and how to run a successful big data analytics projects. This foundation course will also introduce you to two of the most popular technologies in big data processing (Hadoop and MongoDB).

After completing the course, you will be equipped with practical knowledge that can be used as a starting point in your organizational big data journey.

Topics for this course

• Module 1 Big Data Fundamentals – history, overview, characteristics, the three V’s of Big Data (Volume, Velocity & Variety), the impact of Big Data on business, and success stories
• Module 2 Big Data sources – Enterprise data from systems (Oracle, SAP), data warehouses, structured and unstructured data, social media data sources, public data sources
• Module 3 Big Data & Data Science – how to get value out of Big Data, the workflow process for approaching data science problems, and setup of projects.
• Module 4 Big Data Technologies – overview of Big Data technologies Hadoop, MapReduce, MongoDB, and Document Databases
• Module 5 Big Data Applications – uses of Big Data with examples (Twitter Sentiment Analysis, Network Log Analysis, and Security & Intelligence)
• Module 6 Big Data Privacy and Ethics – compliance and its challenges