While culture and data quality are important to building a solid data strategy, platform innovation is essential to future-proof that strategy. By bringing new sources of data, diversifying underlying technologies and applying new technical approaches, you can deliver much sharper, near real-time insights across the enterprise.
Where can companies find new data sources to feed this innovation? We recommend tapping into unstructured data sources that may have been untouched until now. For example, within legal limits, manufacturers can use camera images and video to assess quality and functionality of what’s being manufactured on the production line.
Or, if companies have already exhausted the valuable data sources within their walls, they can look to bring in trusted, third-party data to complement or fine-tune the insights they already have. They can also look to incorporate data from the edge, whose real-time analysis of sensor data can help, for example, predict maintenance for a variety of industrial and energy production equipment to improve operations.
Then, think about the ingestion and management of that data. Five to 10 years ago, most organizations used batch processing through extract/transform/load (ETL) processes. But new platforms and capabilities are rapidly becoming available and making processes more efficient and effective. And as new open-source techniques become more mainstream and commercially supported, it’s easier for businesses to take advantage of the latest innovation and data sets in a turnkey manner.