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Data Analysis

What is Data Analysis?

Data analysis aims to gather useful information so it can be used and analysed in decision making processes. The process itself involves cleaning, transforming and modelling data to create a detailed analysis. Once this is completed, businesses and managers can extract the valuable information and make an educated decision based upon the data analysis. Data analysis tools are regularly employed to make it easier for businesses to process and manipulate data, evaluate the relationships and correlations between data sets, and recognise patterns and trends for interpretation.

In business, data analysis is most commonly employed when the business has reached a stagnant or deteriorating level. It is then essential that the business managers can look back and acknowledge previous mistakes to decipher a plan to avoid repeating those same mistakes. Even if the business is growing, data analysis can be beneficial to ensure the continued success of the company.

What is the process of Data Analysis?

The process of data analysis is simply the collecting of information using a proper application or tool. This subsequently permits the investigation of data in order to find a pattern or trend within it. Based on the information and data gathered, it is possible to make informed decisions to reach high-accuracy conclusions.

Why is Data Analysis Important?

Data Analysis is essential to the success of any business. With regard to a company’s customers, using data analysis to get a well-rounded vision of all customer-related aspects will enable you to understand which channels they use to communicate with you, their demographics, interests, habits, purchasing behaviours and more. The benefit of this is that it will increase the success of your marketing strategies by allowing you to identify potential new customers and avoid targeting the wrong ones. It will also enable you to track customer satisfaction by analysing customer reviews.

With regard to managers, data analysis is beneficial as it helps you to base business decisions on facts rather than intuition. An example of such is that a manager will be able to detect growth opportunities for the business and tackle uncommon situations before they arise.

Data analysis consists of the following phases:

1. Data Requirement Gathering: Decipher the purpose of your data analysis and what you would like to receive from it. You must also decide what to analyse and how to measure it.

2. Data Collection: Work out what you need to measure and predict your findings. Ensure to keep a log of the data collected, their data and source.

3. Data Cleaning: Clean your data by removing any data from your log that is irrelevant to the aim of your analysis, duplicate records or errors.

4. Data Analysis: As you begin to analyse your data, you may discover that you have the exact information you need, or that you need to collect more. Use data analysis tools and software during this phase to help you understand, interpret and derive conclusions based on the requirements.

5. Data Interpretation: Once you have analysed the data, you can interpret your results. Use the results to decide your best course of action going forward.

6. Data Visualisation: Data visualisation often comes in the form of charts and graphs, so it is easier for us to process and understand. By observing relationships and comparing datasets, you can discover meaningful information such as unknown facts and trends.

To Discover More About Data Analysis:

What is Data Analysis

Business Guide to Data Analysis

Top 4 Data Analysis Techniques

What, How and Why to do Data Analysis

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