As per the survey conducted, it is revealed that C-level executives think that big data is the vital cure for each of their business ills.
But, the fact is that regardless of how progressive your IT infrastructure is, the data will not offer you with a handy solution unless you know the answer to some specific question.
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Best Tips for Our Clients to Ask the Right Data Analysis Questions:
Here, we are helping our clients to solve hundreds of their data analysis problems. Our experience says that data analysis can have a great success if you have clear thoughts on the questions you want to ask. Here are some data analysis questions listed that will surely help you.
1. What you actually desiring to find out?
It is always essential to have an evaluation of your business first. Have a discussion company-wide what KPIs are much appropriate for your business & how they previously cultivated. Think of the way you desire them to grow further. Can you affect this growth? Find out where such changes can be done. If there is nothing to get changed, the data analysis is senseless.
2. Where will your data come from?
Our second step is to find out data sources you require sticking into each of your data, choosing the fields you will need, releasing some room for data you might possibly want in the future, and collect all the detail into the single place. Stay open minded on your data sources in this stage –every department of your firm, sales, IT, finance, etc., have the power to provide insights.
You are not needed to worry if you feel like the profusion of data sources makes things look complex. Our further step is to “edit” the sources as well as ensure that their data quality is up to the standards, which will dispose of some of them as convenient choices.
3. What standard KPIs will you use that can help?
After having yourself done with your questions of data analytics, you require having some standard KPIs which you can utilize to measure them rightly. For instance, let’s say you desire to know which of your PPC campaigns last quarter performed the best. As the expert reminded us, “did the best” is very vague to be expedient. Did the best in relation to what? Driving profit? Driving revenue? Giving the most ROI? Providing the inexpensive email subscribers?
Each of these examples of KPI can be valid options. You are just needed to choose the right ones primarily and get them in agreement company-wide (or even inside your department).
4. How can you have the assurance of the data quality?
Insights as well as analytics depending on the shaky “data Foundation” will provide you… well, poor analytics and insights.
Bear in mind that your data analysis questions are devised to have a clear view of genuineness as it relates to your business being much beneficial. If your data is inappropriate, you are supposed to see a partial view of reality.
Therefore, your further step is to “clean” the data sets with the aim to discard outdated or wrong information. Moreover, this is a right time to add extra fields to your data with the aim to make it more comprehensive and useful. This can be pretty annoying but are very important.
When are done the legwork to verify your data quality, you will need to build yourself the valuable asset of precise data sets that can be joined, transformed, & measured with statistical approaches.
5. Knowing About the Statistical Analytics Techniques that You want to Apply
You can have a lot of statistical analysis techniques to pick out from. However, as per our experience below are best statistical techniques are greatly utilized for business data analysis:
- Regression Analysis– it is a statistical procedure for estimating the correlations and relationships among variables.
More precisely, regression analysis assists one to know how the typical rate of dependent variable varies if any one of the independent variables is changes, while further independent variables stay fixed.
- Cohort Analysis– this method enables you to effortlessly compare how different cohorts or groups of customers, behave with the time.
Cohort analysis tools provide you clear and quick insight into consumer retention trends & your business perspectives.
- Prescriptive and Predictive Analysis– it is based on analysing historical and current data sets to forecast future possibilities, including risk assessment and alternative scenarios.
Methods like autoregressive integrated moving average (ARIMA) and artificial neural networks (ANN), time series, periodic naïve approach & data mining find wide application in data analytics at the present time.
6. Having a Thought on Data Visualization.
Your calculations are done and data is clean, but you are not done yet. You can possess the most valued insights of the world; however, if they are presented poorly, your potential audience won’t attain the effect from them that you are actually hoping for.
And we do not reside in a world where just having the correct data is the sufficient thing. You need to influence other decision makers inside your firm that this data is:
- Urgent to act upon
Influential presentation helps in each of these areas. We can have dozens of data charts to pick out from and you can either spoil all your data-crunching efforts through choosing the wrong data visualization or provide it with an additional boost through picking out the appropriate data visualization type.
7. How can you develop a right data-driven culture?
With the aim to rightly incorporate this data-driven method to operating the business, each of the individuals in the company, irrespective of the department they serve in, necessitates knowing how to begin asking the appropriate data analytics questions.
They should know why it is imperative to place data analysis in the primary place.
However, just hoping and wishing that others will lead the data analysis is a method doomed to fail. Honestly, asking them to utilize data analysis (devoid of showing them the advantages first) is also improbable to succeed.
Show your internal consumers that the habit of consistent data analysis is an inestimable benefit for optimizing the performance of your business. Try to build an advantageous dashboard culture inside your firm.
Data analysis is not a way to discipline your employees as well as find who is accountable for failures, but to enable them to increase their performance & also self-improve.