Data analysis is a process of collecting, cleansing, transforming, and modeling data in order to glean useful information. Extract actionable, relevant information in order to make informed decisions. This process helps reduce the risks inherent in decision-making by utilizing useful insights and statistics that are often presented in charts, images, tables and grpahs.
Data visualization is the graphical representations of data through utilizing charts, plots, maps, infographics, animations etc. It is an extremely effective tool for communicating information hidden in data. Identify patterns, trends and outliers in large data sets in an easy to understand and digestable form.
RMC will help design and develop data collection, cleansing, transformation and visualization processes. Our expert teams for each of these steps will determine the optimal solution and deploy the right solution based on the present and future state of the available technolgoy solutions.
Design and implement ETL/ELT processes as well as other data colleciton mechanisms. Data consolidation solution needs to be flexible, robust and scalable in order for ever changing data landscape. This step begins with the determination of business goals, discovery of existing data collection solutions and the connectivity between systems. Data security and governance considerations are paramount in the final design of any solutions.
No analysis or visualization is useful if they are based on erroneous data. So, any solution would involve necessary cleansing process and safe-guards to ensure any inaccurate information is trapped and filtered out before entering into the data model.
Often times data needs to be transfomed in the desired form dictaed by the data model before entering into the databse, warehouse etc. Successful utilization depends on an effective data transformation process. RMC would evaluate the steps necessary for optimal transformation.
In this step all necessary reports, dashboards involving appropriate analytics and BI platform would be developed. It may be required to upgrade existing data visualization process by optimizing at different architectural levels e.g., Data sources, data models, visualization techniques, connections between data sources etc.
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