Data Science is relevant in all possible business processes. It impacts decision-making and provides unending opportunities. It offers sophisticated, flexible approaches to any challenge to help achieve any goal. Data science combined with an efficient platform offers contemporary analytical solutions for sustained success. Personalize interactions; identify probable anomalies; integrate data to holistically identify, analyze risk, eliminate false positives; and reduce the uncertainty of outcomes.
Data wrangling, sometimes referred to as data munging, is the process of transforming and mapping data from one “raw” data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics. A data wrangler is a person who performs these transformation operations. This may include further munging, data visualization, data aggregation, training a statistical model, as well as many other potential uses.
Data engineering organizes data to make it easy for other systems and people to use. Companies create data using many different types of technologies. Each technology is specialized for a specific purpose – speed, security, and cost are some of the tradeoffs. Application teams choose the technology that is best suited to the system they are building. Data engineering must be capable of working with these technologies and the data(structured/unstructured/semi-structured) they produce. At Preferhub, data engineers thinks about the end-to-end process as “data pipelines.” Each pipeline has one or more sources, and one or more destinations. Within the pipeline, data may undergo several steps of transformation, validation, enrichment, summarization, or other steps. Data engineers create these pipelines with a variety of technologies such as: ELT, Python, SQL, Hadoop, etc.
Data storage refers to enterprise storage or storage used for recording media to archive data using computer or other devices. The prevalent forms of storage either hard data storage such as file storage, block storage, and object storage or remote data storage such as cloud computing serve different purposes that users access data.