Five steps to jumpstart your data integration journey - Journey to AI Blog

As coined by British mathematician Clive Humby, “data is the new oil.” Like oil, data is valuable but it must be refined in order to provide value. Organizations need to collect, organize, and analyze their data across multi-cloud, hybrid cloud, and data lakes. Yet traditional ETL tools support only a limited number of delivery styles and involve a significant amount of hand-coding. In turn, enterprises are increasingly looking for machine-learning-powered integration tools to synchronize data for analytics, improve employee productivity, and prepare data for analytics. To achieve this, we will examine five steps an analyst at a fictitious financial services company, named Raviga, will take to be successful in their data integration project using IBM DataStage on IBM Cloud Pak for Data. 1. Ingest the Data Data must be ingested before it can be digested. First, the Raviga analyst needs access to its data sources before it can procure analytics. They need to access their data from multiple sources…