Data Analytic Concepts
The course is part of this learning path
This course explores the different concepts behind data analytics. It will provide you with a clearer understanding of what data analytics actually is and how it allows you to collate, store, review, and analyze data to help drive business decisions through insights that have been identified.
If you have any feedback relating to this course, please contact us at firstname.lastname@example.org.
By the end of this course, you will have an understanding of:
- Different analytic concepts
- Data types, including structured, semi-structured, and unstructured data
- When you should use data analytics within your business
- The process behind running analytics against data
This course is ideal for those looking to become data scientists or solutions architects. Also, if you are studying for the AWS Data Analytics - Specialty certification, then this course would act as a great introduction to the topic itself.
As this is a beginner's course, all concepts will be explained throughout the course. Any knowledge of AWS data analytic services would be advantageous, but not essential.
Hello and welcome to this lecture which will provide you with an understanding of different analytic concepts to help you understand the principles behind many of the AWS services and architectures that are used when implementing data analysis solutions
Basically, analytics or data analytics is the science of data transformation, transforming data into meaningful information and insights. Here we refer to data as any input you have like a spreadsheet, a CSV file, historic sales information, a database, raw research data, essentially, any data that you may have. With this basic concept in mind let's explore a bit further the analytics concept.
Everything starts with the questions to the problems you have, using analytics we want to solve these problems by selecting the right tools to collect or clean the data in an appropriate fashion. As an input for our analytics, we may have data which can be organized into different categories. For example, we have qualitative and quantitative data, and classification in the manner of structured and unstructured data. If you are new to these concepts, don’t worry as I’ll explain them in a minute.
Then we have the analytics process itself which takes this data as input, then enters a statistical and mathematical model, classifies, extracts correlations, and organizes the data in order to answer your questions to the problems you want to solve.
Stuart has been working within the IT industry for two decades covering a huge range of topic areas and technologies, from data center and network infrastructure design, to cloud architecture and implementation.
To date, Stuart has created 90+ courses relating to Cloud reaching over 100,000 students, mostly within the AWS category and with a heavy focus on security and compliance.
Stuart is a member of the AWS Community Builders Program for his contributions towards AWS.
He is AWS certified and accredited in addition to being a published author covering topics across the AWS landscape.
In January 2016 Stuart was awarded ‘Expert of the Year Award 2015’ from Experts Exchange for his knowledge share within cloud services to the community.
Stuart enjoys writing about cloud technologies and you will find many of his articles within our blog pages.