Data Analytics
Data Analytics is a process of collecting, transforming, cleaning, and modeling data with the goal of discovering the required information. The results so obtained are communicated, suggesting conclusions and supporting decision-making. Data visualization is at times used to portray the data for the ease of discovering useful patterns in the data.
Data analytics can help businesses understand who their customers are, what they want, and how they interact with the business. It can also help business understand their own internal processes, identify bottlenecks and inefficiencies, and find new opportunities for improvement.It is a powerful tool that can help businesses improve their performance and better serve their customers. With the right data and the right analytics, businesses can gain insights that they never would have found otherwise.
Data analytics enables employees to view data in context, which helps them to better understand the data and make better decisions. By viewing data in context, employees can see how the data relates to other data points and understand the data in a more holistic way. This helps employees to make better decisions about the data and to better understand the data.
How Manak Process
Data Requirements Specification The data required for analysis is based on a question or an experiment. Based on the requirements of those directing the analysis.
Data Collection Data Collection is the process of gathering information on targeted variables identified as data requirements. The emphasis is on ensuring accurate and honest collection of data. Data Collection ensures that data gathered is accurate such that the related decisions are valid. Data Collection provides both a baseline to measure and a target to improve.
Data Processing The data that is collected must be processed or organized for analysis. This includes structuring the data as required for the relevant Analysis Tools.
Data Cleaning The processed and organized data may be incomplete, contain duplicates, or contain errors. Data Cleaning is the process of preventing and correcting these errors.
Data Analysis Data that is processed, organized and cleaned would be ready for the analysis. Various data analysis techniques are available to understand, interpret, and derive conclusions based on the requirements. Data Visualization may also be used to examine the data in graphical format, to obtain additional insight regarding the messages within the data.
Communication The results of the data analysis are to be reported in a format as required by the users to support their decisions and further action. The feedback from the users might result in additional analysis.
