Description
Expand your ability to work with structured and unstructured data to drive a successful analytics practice.
Objectives
- Identify opportunities, processes, and necessary data for solving analytical problems.
- Apply data profiling and data cleansing techniques to available data.
- Use data preparation and enrichment tools.
- Use ETL (extract, transform, load) tools.
- Compare data warehousing techniques.
- Use data warehousing and data management tools.
- Align the outcomes of your data analytics practice with your organization's strategic direction and create value
Highlights
- Defining value and tying analytics to value-driven business cases
- Understanding the characteristics of data and how they can be leveraged to gather insights from information
- Identifying project constructs for data analytics
- Identifying different types of data with which analysts will be expected to interact
- Profiling data for accurate analysis initiatives
- Understanding tool capabilities for working with data
- Cleansing data with appropriate tools to increases analytics accuracy
- Managing data quality and integrity
- Extracting, transforming, and loading data
- Implementing a data warehouse
- Managing the data life cycle
- Creating and using different types of data models
- Tools for working with both structured and unstructured data