Industry executives and experts share their predictions for 2020. Read them in this 12th annual VMblog.com series exclusive.
By Peter Bailis, founder and CEO of Sisu
A look into analytics: why are our critical business metrics changing?
From our work with customers seeking this promised golden age of data, we see four major shifts gaining momentum in 2020. Starting with the rise of a new analytics stack, we’ll also see a shift in focus away from dashboards to a more diagnostic approach to analysis, a demand for more useful facts, and the emergence of a new role – the Operational Analyst.
1. The rise of a new, more flexible analytics stack. Starting with an investment in cloud data warehouses like Redshift, Snowflake, and BigQuery, companies are also adopting modern data pipeline and ETL tools like Fivetran and Stitch to funnel more data into these structured storage solutions. What’s next? Companies will rebuild their diagnostic tools to cope with the influx of richer data.
To handle the dozens of data sources and near-real time data volumes in a typical organization, IT and data teams will rebuild their analytics infrastructure around four key layers:
- A cloud data warehouse, like Snowflake, BigQuery, Redshift, or Azure
- Data pipeline tools like Fivetran and Stitch
- Flexible dashboarding and reporting tools like Looker
- Diagnostic analytics tools to augment the abilities of analysts and BI teams
Beyond 2020, governance comes back to the forefront. As platforms for analysis and diagnosis expand, derived facts from data will be shared more seamlessly within a business, as data governance tools will help ensure the confidentiality, proper use, and integrity of data improve to the point they fade into the background again. In 2020, we’ll see a shift in how companies use and perceive analytics.
2. Diagnosis over dashboarding. Combined with this infrastructure change, we’re seeing board rooms asking why metrics are changing and what those changes mean for day to day business operations. Competitive moats are being built (and crossed) based on the effective use of data, and successful companies will need to stop thinking about their data as a passive archive and more of a competitive asset.
3. Rise of the Operational Analyst. The future of data analytics is that we’ll see the rise of the operational analyst. Data is not the sole domain of the data scientist anymore. Everyone in an organization will start acting more like a data analyst on a daily basis, and we’ll see new skills and tools focused on specific use cases emerge. Analyzing trends, changes, and using data to make impactful decisions will become the new employee norm and expectation. It is no longer limited to the business analyst or the marketing analytics team.
4. Insights cease to be interesting. Find the facts. In 2020, we’ll see more context within data, creating actionable data for a variety of departments within a company, requiring tech savvy employees and tools. Ultimately, the platform that can enable more decision making processes will win the market and lead to new ways to answer business questions. This shift will require collaboration and data and analytics teams to move back towards the business, reversing the swing of centralized data teams over the last 5 years.
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About the Author
Peter Bailis is the founder and CEO of Sisu, a data analytics platform that helps users understand the key drivers behind critical business metrics in real time. Peter is also an assistant professor of computer science at Stanford University, where he coleads Stanford DAWN, a research project focused on making it dramatically easier to build machine learning-enabled applications. He holds a PhD from the University of California, Berkeley, for which he was awarded the ACM SIGMOD Jim Gray Doctoral Dissertation Award, and an AB from Harvard College in 2011, both in computer science.
