With the need for trusted data at all levels, the return on investment for Data Observability takes center stage for the value of cleaner data. The ROI is based on how much cost savings can be gained to ensure quality data – some analysts say it can add up to 40% of a data engineer’s time. Add machine learning to the mix for speedier validation or reconciliation and Augmented Data Quality shows its importance for automated data quality workflows. In 2023, trusted data will be the mantra across every enterprise.
As a concept, data mesh did create dialogue around the value of decentralized data into actionable data domains, but we always knew more was needed. In 2023, the reality is now software platforms can manage data-as-a-product (as opposed to data assets) and create an internal data marketplace where the transaction of producers feeding consumers replaces simplistic target and source frameworks.
The need for managing metadata within the context of a powerful data catalog will become the main task of data governors, who are moving beyond just controlling data access with identity management systems and federated governance. In addition, ethical AI will gain steam as the automated management of standards test every data set in the entire workflow. Of any group in the data system, 2023 is the year for data governors with their evolving role for successful data management.
Finally, business users will be able to access the data sets they want more than ever before. Systems will be measured on a “people-first” basis, where data management will be judged as much for access to data sets as the inherent value of the data itself. The payoff? In 2023, there will be a shift to the right for data decision-making solutions that ease the burden for the lack of data scientists.
In 2023, the number of customers using multi-cloud networking software (MCNS) for multiple functions will increase 30% to more than 3,000, according to one major analyst. This changes the architectural landscape for data management because greater flexibility will be needed and traditional loading using simple cloud tools (e.g. Glue, ADF) will struggle to meet all cloud needs. Simply stated, data integration must do much more than ETL, ingest or load – those that embrace multi-cloud management will be the winners.
With the unprecedented growth of Databricks and its leadership in the Cloud Database Management System (CDBMS) area, the implementation of Delta Lake as the open-source layer on top of the existing data lake has proved its worth. However, data architects now have to be careful to ensure a smooth User Interface and effortless data management system to make it all work. It’s all coming together in 2023.
Beyond the classic steps of making data better (i.e., discovery, structuring, cleaning, enriching, validating, publishing) Data Wrangling actually removes risk by preparing data in a reliable state before learning. Without this critical phase, how can we even trust any modeling approaches or algorithms a Machine learning scientists that embrace the data and not just the model will be the most credible as data scales to even better results and predictions. Giddy up for better data in 2023.
While analysts say that less than 10% of companies are mature when it comes to D&A, there is still a perceived value gap in how predictive analytics add real value to companies. Analysts will be challenged to produce impactful insights and will use more Business Intelligence (BI) fabrics and tools to get an edge on how decision-makers use insights. In 2023, we will see greater emphasis on valuable insights as opposed to boring dashboards.
Smart Choices for 2023. Data management and decisions in 2023 will be more critical than ever before. RightData looks forward to these challenges and talking with you about your ideas and needs. Check out RightData at www.getrightdata.com for both the knowledge and the software that secures a better future today.