Decision Making With Data Analysis

Data analysis is the process of collecting, organizing, and analyzing data to conclude your business. It can be used for decision-making and various other uses such as marketing, scientific research, or business intelligence. People use many different tools for data analysis, including spreadsheets, databases, software like Tableau, and Excel. The steps below will help you get on with better decision making for a data analysis project!

Defining your question

If you want to get the most out of your business data, it is essential to understand what you would like to get out of the project. This should be a straightforward, concise question that you are trying to answer with your analysis.

For example, a question could be with the rising cost of materials to produce this product can we reduce our staff cost without compromising the quality of the product?

Setting up clear Measurement Priorities.

It’s also essential to set data priorities for what you want to measure. This will help you decide which data points are the most important and relevant in your analysis. Your measurement priority list could include things like profit, the number of customers or staff cost.

Selecting Data Points

Now that we have defined our question, determining measurements priorities, it is time to select a data point- one piece of information from each category on your measurement priority list, For example, Revenue, Number Of Employees, Total Cost To Produce Product)

Investigating the DataPoint(s) Selected

In this step, take some time to think about how people might answer the questions posed by these categories and then make decisions based on all available data points. So how will I measure it in short? For example, you may look at time frames, your basic units to measure and ask yourself what other factors are needed.

Collecting the data

Having defined the main question you are looking to answer, it is time to get all the data together. Your data is most likely coming from various sources, and it will need to be organized, summarized or filtered before you can make any sense of it. Here are points to keep to mind:

  • Make sure before you collect the new data, you need to work out what data you can get from an existing database that is to hand. Start with this first as it is the easiest
  • Create a storage and naming system before you start getting the data. This will save you so much time in the past and will reduce duplicates
  • If you find you need more data from interviews or observations, then make sure to create a template to make sure they are consistent.
  • Keeping a good log of all the data, including dates and source notes and making sure you do this as you go. This will help you validate your findings.

Time To Analyze Data

The Data Analysis Process is the process of making sense of data. It can take a long time to do this, which means it needs to be done in stages and understand what you are looking for at each stage. There are various ways to accomplish this:

Analyzing data comes in many shapes or forms depending on what exactly interests one’s findings most: plotting it out and finding patterns or through complicated calculations using excel programs like pivot tables- which lets one analyze their personal preferences based on means/maximums/minimums.

When you’re processing data, it’s common to find that the information is just not what you need. You can either go back and revise your original question or spend more time collecting new data. In any case, this initial analysis of trends and outliers helps focus your efforts on asking a better question to make objections from others irrelevant!

The most common tool people use excel, which is a significant decision-making tool problem you will find is when you come to collaborate with people, formula issues to present the findings. This is when software like Tableau comes it, one of the market leaders in data visualization.

The power of Tableau is that it can handle the complexity of data without sacrificing ease of use. This means that people who are not traditionally numbers-savvy will be able to work with Tableau and get meaningful insights from their data.

To truly unleash the power of Tableau and to save you time is to get the help of a tableau consultant who can help you revolutionize how you use and visualize the data. Helping you get to the answer to your question faster and allowing you to display the data that everyone understands, even the non-analytical people.

The results

So you have now analyzed the data. You can use Tableau to visualise the data and then share it with people outside of your organization so they can see how you have come to this solution or Findings. How do you know if your findings are conclusive? If the data holds up to all your questions if it does, then the last step is to plan on how you will act upon this data.

Data analysis is an essential part of many businesses. Whether you’re using it to make decisions or looking for ways to improve your marketing strategy and drive more sales, data analysis can be a valuable tool in the right hands. The steps above are just the beginning of what you’ll need to do to conduct a successful business data analysis.

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