Big data gets much attention for the changes that it brings to the field of data analytics. We must also realize that it changes the game for data management practitioners. Data architects, data engineers, and data analysts—nearly anyone who works with data—need to learn new skills to succeed in the age of big data.
Big data is an important topic for modern analytics, yet it is continuously evolving. Achieving good return on your big data investment requires strategy that focuses on purpose, people, and process before exploring data and technologies. Strategy drives planning and architecture to ensure that big data complements and does not disrupt the existing BI and analytics environment. There are many technologies to leverage the power of big data, but data and technologies alone don’t create insight and value. The real question is how to engage in the big data journey and develop a viable big data strategy. This requires a roadmap to plan, build, and execute.
With strategy in place the right technologies become the path to value. Data management and business insights both depend on technology. Machine learning and deep learning technology is at the leading edge of big data analytics. Hadoop is the widely accepted open source technology that establishes the baseline for big data management.
The Must-Have Skills for Big Data Practitioners workshop will cover essential techniques and best practices for leveraging the power of big data over three days of in-depth, interactive training.
Your Team Will Learn
- Key characteristics of big data and why “big” is not among the top five
- The hidden structures of unstructured data and the common types of big data sources
- Value opportunities and common applications for big data
- How to define, refine, and apply a big data roadmap
- The opportunities, technologies, and techniques of machine learning and deep learning
- Key considerations for implementing machine learning
- Hadoop components and architecture
- Hadoop configuration, administration, and management
- How to use common Hadoop tools
- Business and data analysts
- Data engineers with big data responsibilities
- Analytics program and project managers
- BI and analytics architects, designers, and developers
- Anyone with a role in analytics or big data
- Anyone with an interest in Hadoop, ranging from “Hadoop curious” to those who are actively involved in implementation