As we move into 2020, data management will continue to advance and develop efficiencies that will make the job of having data ready for business purposes faster and more reliable than ever. While the data management space is a diverse field in its practices, there are four trends that will be forefront in 2020:
- Data Orchestration – The uniting of data integration, API integration, and data movement to support DataOps techniques. This involves combining multiple technologies to deliver a single data flow application to orchestrate data-related activities across varied locations on-premises or in the cloud.
- Data Discovery – Acknowledged as important “glue” to enterprise software, delivery of a common catalog for finding, provisioning, securing and understanding data and other objects is important to customers. Further, this discovered insight through application of advanced analytics delivers the ability to automate mundane data management tasks and find value in data that previously had been too difficult to discern.
- Data Preparation – To expand data manipulation activities to a wider audience, development of advanced data transformation using AI to automate cleansing and blending will empower non-technical users.
- Model Management – The market will see growth in model management – not just management of proprietary or open source models on their own but managing those models together within one application. With most analytical models never making it into production or possibly outliving their usefulness (known as model decay), organizations will need the ability to easily register, modify, track, score, publish, govern and report on analytical models.
So, what are the biggest challenges facing data management going into 2020?
- According to the World Economic Forum, it is predicted by 2020 that the amount of data we produce will reach a staggering 44 zettabytes. (For example, by 2020 it is predicted that 500 million tweets and 294 billion emails will be sent daily.)
- Big data is at its core about getting insights on more data/from more sources than ever before. The promise of big data never came from simply having more data – and from more sources – but by being able to develop analytical models to gain better insights on this data.
- With all the work being done to advance the work of analytics, AI and ML, it is all for not if organizations do not have a data management program in place that can access, integrate, cleanse and govern all this data.
And last, what will see in consumer data privacy/protection in 2020?
- The increasing amount of privacy/protection laws seen throughout the world have prompted organizations to develop data governance programs that include data privacy by default. However, organizations need to be proactive with their privacy standards and programs. If not, they will be caught out of compliance for various laws and ultimately not trusted by their customers.
- While addressed within the GDPR, the use of advanced analytics and AI for decision making is ripe for further laws. With such concerns as biased decisions based on race, sex, nationality and age (to name a few), organizations will need to be more aware and transparent as to how their developed algorithms and AI are making decisions that could impact their customers.
Todd Wright, Head of Data Management and Data Privacy Solutions at SAS, is a respected expert on data privacy and management. You’ll find his insights on the topic featured in publications like the Wall Street Journal, InformationWeek, Datanami, insideBIGDATA, TechRepublic and more.