Apache PigPig is a platform for creating query execution routines on large, distributed data sets. The scripting language used is called Pig Latin (No, I didn’t make it up, believe me). Pig is supposedly easy to understand and learn. But my question is how many of these can one learn?
Explore Data & Analytics Statistics
- 55 percent of North American businesses have adopted big data analytics.
- 29 percent of investment professionals use search trends to derive data.
- Data warehouse optimization is considered the most important big data analytics use case, and is considered critical or very important by 70 percent of businesses.
- 40 percent of businesses say they need to manage unstructured data on a frequent basis.
- 53 percent of CEOs consider themselves the primary leader of their company’s analytics agenda.
- 73 percent of businesses consider Spark SQL critical to their analytics strategies as a big data access method.
- Nearly 50 percent of businesses say big data and analytics have fundamentally changed business practices in their sales and marketing departments.
- 60 percent of businesses believe it is harder to source talent for data and analytics positions than for any other roles
- 30 percent of businesses consider the Spark software framework critical to their big data analytics strategies.
- The number of IT professionals using descriptive and predictive analytics grew from the mid-40th percentile to high 60th percentile between January 2018 and January 2019.
Check Out Data & Analytics Tools
Recent Blogs on Data & Analytics
- Winning strategies for Data Governance maturity
- Exploring the Decomposition Tree Visual in Power BI
- Five Questions You Need To Answer To Get The Most Out Of Power BI
- Six Reasons to Consider Power BI Premium
- The Value of Data Management
- A 360-Degree Customer View: Personalizing the Consumer Journey
- Data Governance: Lessons learned for best practices
- Part 2: How the Snowflake Cloud Data Platform transforms organization?
- Why choose Snowflake Cloud Data Platform?
- The Benefits of Data Lakes for Financial Services