Rapid Fire on Data Analytics

Data analysts require inputs from the business owners and a collaborative environment to operationalize analytics. To create and deploy predictive models in production there should be an effective, efficient and repeatable process. Without taking feedback from the business owner, the model will just be a one-and-done model. The best way to answer this question would … Read more

From a given dataset for analysis, it is extremely important to sort the information required for data analysis. Data cleaning is a crucial step in the analysis process wherein data is inspected to find any anomalies, remove repetitive data, eliminate any incorrect information, etc. Data cleansing does not involve deleting any existing information from the … Read more

A good data analyst is the one who understands how changing business dynamics will affect the efficiency of a predictive model. You must be a valuable consultant who can use analytical skills and business acumen to find the root cause of business problems. The best way to answer this question would be to say that … Read more

Data Profiling, also referred to as Data Archeology is the process of assessing the data values in a given dataset for uniqueness, consistency and logic. Data profiling cannot identify any incorrect or inaccurate data but can detect only business rules violations or anomalies. The main purpose of data profiling is to find out if the … Read more

Data analysis deals with collecting, inspecting, cleansing, transforming and modelling data to glean valuable insights and support better decision making in an organization. The various steps involved in the data analysis process include – Data Exploration – Having identified the business problem, a data analyst has to go through the data provided by the client … Read more