Data Analysis Data analysis is the process of examining data so that we can get quicker and clearer insights into our business processes.

There are many reasons why we analyze data and one of those is that it helps us make more informed business decisions.

Finding patterns and trends in the data and identifying actionable insights.

It helps provide insight to goals and targets that have been set for our business or for our staff and it also provides better understanding of the financial costs and profit margins within our business.

Data analysis can be quantitative which means it's measuring values numbers and so on.

Or it can be qualitative. This is where it cannot be objectively measured or counted.

Quantitative data is much easier to analyze.

Qualitative data takes a bit more work and requires some more specialist software, but it is important part of data analysis, and it does reveal some hidden insights.

There are four types of data analysis. It can be descriptive, diagnostic, predictive, or prescriptive.

Descriptive analytics tells us what has happened in the past. It uses historical data and it will highlight a problem but not solve it. So it'll tell us for example that there has been a dip in the sales in June or July.

Diagnostic analytics is also using historical data. It's retrospective.

But it doesn't just tell us what has happened. It seeks to answer why that has happened.

So it may involve diving deeper into the data looking for anomalies and maybe putting into context with some more information. So if we were to analyze the data further, we would discover that there was less expenditure on advertising and May and April which perhaps produced the dip of seals in June and July.

Predictive Analytics looks to the future.

So it's forecasting it tells us what is likely to happen next and relies on mathematical algorithms to do this.

Prescriptive analytics also looks to the future and it uses predictive models. But as well as telling us what might happen it also provides a pathway telling us what we could do to perhaps prevent something from happening.

There are many popular tools for data analysis Power BI is one of the most common and popular tools used today.

Tableau is another one, that's very popular. Qlikview. Even Microsoft Excel. They're all used to help provide insight into the data, to establish and discover patterns and trends that you can't otherwise see in rows and rows and columns of data.

And that's commonly used today is python. It does require some programming knowledge, but it will also provide insight into the data by producing patterns and trends in some visuals.