Maximise the value of your data whilst reducing cost and complexity.
Many companies work in silos and business stakeholders are divorced from the data engineers and analysts. This means that organisations do not use their data effectively to achieve the best business outcomes.
A non-standard approach to Data Management means that businesses often suffer from tunnel vision when solving specific, local issues and thus implement fragmented solutions.
This ad hoc approach to business solutions leads to a lack of standardisation and consequently increases risk and cost whilst not guaranteeing data quality.
Kinaesis DataOps is a data management approach that builds a unified, automated process encompassing MDM, distribution, quality control, privacy and analytics. It bakes change control and metadata maintenance into the delivery process. Furthermore, it addresses every aspect of data ownership, stewardship and exploitation.
Kinaesis aim to provide standardisation and automation to not just improve agility, reduce risk and cost but also to ensure that data quality and lineage information is always delivered alongside decision making data.
We utilise our DataOps methodology structure to catapult businesses to the highest levels of maturity for their operating model, architecture, data quality, metadata definition, data frequency and master data management.