The once simple world of data preparation—ETL for operational data integration—has become increasingly complex. Terms such as data wrangling and data blending indicate some of the challenges. The exciting work of analytics doesn’t work well until the data is ready for meaningful analysis. The scope of big data, the variety of data uses, and the emergence of business-friendly data visualization and analysis tools all contribute to the complexity.
A recently emerged category of technologies helps to meet the challenges with business-friendly tools for data integration and preparation. When your analytics projects spend more time finding and fixing data than analyzing the data, you really need to make a change. Learn about the tools and techniques that can help individuals and teams—both business and technical—to cleanse, combine, format, and sample data for analytics.
You Will Learn
- The common challenges of data preparation in the age of big data
- Techniques for data preparation that improve both speed and quality of analytics
- The data management and governance benefits of data preparation technologies
- The landscape of tools and technologies for modern data preparation
- To identify the data that is best suited to your analytic needs
- To understand the data and the challenges inherent in that data
- To define and specify data cleansing, formatting, and blending needs
- To understand and apply principles of iterative and adaptive data preparation
- Business managers, business analysts, data analysts, and data scientists who need to accelerate and simplify data preparation activities; BI and analytics developers who face the daily challenges of complex data preparation; technical managers and architects who need to integrate data preparation technologies into the BI and analytics toolkit; everyone who struggles with getting the right data in the right forms for effective analytics.