What Is Data Analysis.pdf - What Is Data Analysis? Data...

What Is Data Analysis?
Data analysis is a process that relies on methods and techniques to taking raw data, mining for insights that
are relevant to the business’s primary goals, and d rilling down into this information to transform metrics, facts,
and figures into initiatives for improvement.
There are various methods for data analysis, largely based on two core areas: quantitative data analysis
methods and data analysis methods in qualitative research.
To explain the key differences between qualitative and quantitative data, here’s a video for your viewing
pleasure:
Gaining a better understanding of different techniques for data analysis, and methods in quantitative research
as well as qualitative insights, will give your information analyzing efforts a more clearly defined direction,
so it’s worth taking the time to allow this particular knowledge to sink in. Additionally, you will be able to
create a comprehensive analytical report that will skyrocket your analysis processes.
How To Analyze Data: Take Advantage Of The Top 15 Data Analysis Methods & Techniques

Now that we’ve answered the question, ‘what is data analysis?’, considered t he different types of analysis
methods, it’s time to dig deeper into how to do data analysis by working through these 15 essential elements.
1. Collaborate your needs
Before you begin to analyze your data or drill down into any analysis techniques, it’s cr ucial to sit down
collaboratively with all key stakeholders within your organization, decide on your primary campaign or
strategic goals, and gain a fundamental understanding of the types of insights that will best benefit your
progress or provide you with the level of vision you need to evolve your organization.
2. Establish your questions
Once you’ve outlined your core objectives, you should consider which questions will need answering to help
you achieve your mission. This is one of the most important data analytics techniques as it will shape the very
foundations of your success.
To help you ask the right things and ensure your data works for you, you have to ask the right data analysis
questions.
3. Harvest your data
After giving your data analytics methodology real direction and knowing which questions need answering to
extract optimum value from the information available to your organization, you should decide on your most
valuable data sources and start collecting your insights – the most fundamental of all data analysis techniques.
4. Set your KPIs
Once you’ve set your data sources, started to gather the raw data you consider to offer potential value, and
established clear-cut questions you want your insights to answer, you need to set a host of key performance
indicators (KPIs) that will help you track, measure, and shape your progress in a number of key areas.