Poor data quality is the single biggest contributor to the poor performance of customer risk-rating models

Poor data quality is the single biggest contributor to the poor performance of customer risk-rating models. Incorrect know-your-customer (KYC) information, missing information on company suppliers, and erroneous business descriptions impair the effectiveness of screening tools and needlessly raise the workload of investigation teams. In many institutions, over half the cases reviewed have been labeled high risk simply due to poor data quality – McKinsey

true cost of ELT

Big data use case: Offloading the data warehouse to Hadoop

The true cost of ELT Today’s business world is demanding more from the data warehouse, because more than ever an organisation’s survival depends on its ability to transform data into actionable insights. However, ELT data integration workloads are now consuming up to 80% of database capacity, resulting in: Rising infrastructure costs Increasing batch windows Longer development cycles Slower…

dmx gui

What is data integration? (building a single view of the truth)

Data integration defined Data integration is a common industry term referring to the requirement to combine data from multiple separate business systems into a single unified view, often called a single view of the truth. This unified view is typically stored in a central data repository known as a data warehouse. For example, customer data integration involves…

ETL ELT architecture

What is ETL?

ETL defined Extract, Transform and Load  or ETL is a standard information management term used to describe a process for the movement and transformation of data. ETL is commonly used to populate data warehouses and datamarts, and for data migration, data integration and business intelligence initiatives. ETL processes can be built by manually writing custom scripts or code, with…