Data Analysis Fundamentals
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Data Analysis Fundamentals Course
Introduction:
The world is becoming more and more data-driven, with endless amounts of data available to work with. Big companies like Google and Microsoft use data to make decisions, but they’re not the only ones.
Data analysis is used also by small businesses, retail companies, medicine, and even in the world of sports. It’s a universal language and more important than ever before. It seems like an advanced concept but data analysis is just a few ideas put into practice.
Data analysis is important in business to understand problems facing an organization, and to explore data in meaningful ways. Data in itself is merely facts and figures. Data analysis organizes, interprets, structures, and presents the data into useful information that provides context for the data.
The main purpose of the Data Analysis Fundamentals training course is to give the attendees practical knowledge and a good understanding of real-world data analysis. The course includes data analysis process, visualizations, data sharing, and creating professional and easy-to-understand dashboards.
Course Objectives:
At the end of this Data Analysis Fundamentals Training Course, learners will be able to do:
- To provide delegates with both an understanding and practical experience of a range of the more common analytical techniques and representation methods for numerical data.
- To give delegates the ability to recognize which types of analysis are best suited to particular types of problems.
- To give delegates sufficient background and theoretical knowledge to be able to judge when an applied technique will likely lead to incorrect conclusions.
- To provide delegates with a working vocabulary of analytical terms to enable them to converse with people who are experts in the areas of data analysis, statistics,cs, and probability, and to be able to read and comprehend common textbooks and journal articles in this field.
- To introduce some basic statistical methods and concepts.
- To explore the use of Excel 2010 or 2013 for data analysis and the capabilities of the Data Analysis Tool Pack.
Who Should Attend?
The data Analysis Fundamentals training course is ideal for:
- Data architects
- Data scientists
- Data analysts
- Accounting and finance professionals, especially those interested in learning and applying data analysis techniques to help their organizations make informed data-driven business decisions.
Course Outlines:
Introduction to data analysis solutions
- Recognize the Value of Using Data to Answer Questions and Address Business Issues
- Explain How Data Has Become the Strategic Business Asset It Is Today
- Data analytics and data analysis concepts
- Introduction to the challenges of data analytics
- Volume – data storage
- Introduction to Amazon S3
- Introduction to data lakes
- Introduction to data storage methods
Velocity – data processing
- Discover Usable Data: Its Source, Type, Value, Quality, Location, and Relationships
- Profile the Data to Determine What Is Important or Relevant
- Organize and Manage Data Appropriately
- Acquire Data from Any Source
- Introduction to data processing methods
- Introduction to batch data processing
- Introduction to stream data processing
Variety – data structure and types
- Introduction to source data storage
- Introduction to structured data stores
- Introduction to semi-structured and unstructured data stores
- Identify and Resolve Problems Associated with Data Collection
- Articulate the Pros and Cons of Data Manipulation
- Determine If Data Samples Are Adequate
- Create a Table That Is Ready to Be Analyzed
Value. Reporting, business intelligence, and Analyzing the Data
- Introduction to analyzing data
- Introduction to visualizing data
- Understand Which Data-Analysis Tools Best Answer Common Analytical Business Questions
- Articulate How the Microsoft® Excel Analysis Tool Pak and Other Programs Can Be Used for Advanced Data Analysis
- Choose the Appropriate Tool and Technique to Analyze Your Data
- Putting the pieces together
Veracity – cleansing, transformation
- Understanding data integrity
- Understanding database consistency
- Introduction to the ETL process
