In an increasingly data-driven world, there is a wealth of information available for analysis. While big companies like Google and Microsoft are known for utilizing data to inform decision-making, data analysis is not limited to them alone.

Data analysis is employed across various sectors, including small businesses, retail companies, healthcare, and even in the realm of sports. It has become a universal language that holds greater significance than ever before. Despite its perceived complexity, data analysis is essentially the practical application of a few fundamental concepts.

Within the business context, data analysis plays a crucial role in understanding organizational challenges and exploring data in meaningful ways. Raw data, in and of itself, consists of mere facts and figures. Data analysis, on the other hand, involves organizing, interpreting, structuring, and presenting data in a manner that provides valuable context and meaningful insights.

The primary objective of the Data Analysis Fundamentals training course is to equip participants with practical knowledge and a comprehensive understanding of real-world data analysis. The course covers the data analysis process, visualization techniques, data sharing methods, and the creation of professional and easily comprehensible 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 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?

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

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