In case you missed it: here’s what happened in data analytics in 2020
Director, Product Marketing, Data and Business Application Platform
2020 was a tough year. As the global pandemic spread and impacted every country, industry, and individual, we turned to data and analytics to help guide us through the unknown. We used data and the cloud to help us understand the spread of COVID-19 while simultaneously digitally transforming industries to offer a safer way for the public to get what they need when they need it. Data and analytics became a critical tool for our essential workers and businesses as they navigated this trying time. Our data analytics team was hard at work to help organizations rethink their business strategy in order to deliver services to their customers.
Everything we heard from customers this year and what we worked on here at Google Cloud reflects this new sense of urgency around using and sharing data across the digital world. Here’s a look back at the four major themes we focused on in 2020 and why they will be more relevant than ever in 2021.
Beyond BI—do more with intelligent services
The amount of data generated today is overwhelming, but an abundance of data doesn’t necessarily equate to useful information. Companies are already employing business intelligence (BI) to get insights from their data and achieve better business outcomes. Now, they can augment their current solutions with AI and machine learning (ML) to analyze massive datasets, recognize patterns, and gain insights that help define the past, the present—and the future.
For example, Looker enables teams to go beyond traditional reports and dashboards to deliver modern BI, integrated insights, data-driven workflows, and custom applications using Looker Blocks. Users also benefit from real-time analytics and aggregate awareness capabilities to stream the most relevant data for high performance and efficient queries. You can use BigQuery ML to build custom ML models without moving data from the warehouse, including real-time AI solutions like anomaly detection. Additionally, the natural language interface Data QnA, announced at Next OnAir, empowers business users to analyze datasets conversationally without adding more work for BI teams.
Open platforms for choice, flexibility, and portability
With the proliferation of SaaS applications and a workload-at-a-time migration mentality, a majority of enterprise cloud architectures are being built with two or more public clouds. This allows enterprises to take advantage of the lowest storage and compute costs, use the most innovative AI and ML services, and provides freedom of portability if needed. That’s why we are committed to being open at Google Cloud.
By 2021, over 75% of midsize and large organizations will have adopted a multicloud and/or hybrid IT strategy.
We’re breaking down silos across different environments to enable our customers to manage, process, analyze, and activate data—no matter where it is. This year, we introduced BigQuery Omni, our flexible, multi-cloud analytics solution that lets you analyze data in Google Cloud, AWS, and Azure (coming soon) without the need for cross-cloud data movement. In addition, Looker’s in-database architecture allows you to query data where it’s located to give you a consistent way to analyze data, even across multiple databases and clouds.
We believe our vision of a multi-cloud, open data analytics future was reflected in this year’s brand-new Gartner Magic Quadrant for Cloud Database Management Systems (DBMS). Google was named a Leader among the furthest three positioned vendors on the completeness-of-vision axis.
In 2020, we also helped organizations like Wayfair migrate their on-prem data analytics open source software to our open cloud. This type of portability allows them to take advantage of cloud scale and costs with Dataproc, while lowering the adoption barrier for their data analytics professionals familiar with Apache Spark, Presto, and Apache Hive.
To strengthen our backup and DR capabilities across all of Google Cloud, Google recently acquired Actifio. Enterprises running critical workloads on Google Cloud, including hybrid scenarios, can prevent data loss and downtime due to external threats, network failures, human errors, and other disruptions.
Scale intelligently without losing control
Data analytics are now mission-critical for many businesses, but how do you respond efficiently to rapid demand and put data into the right hands without driving up costs? Can you achieve flexibility and predictability?
Over the past year, we heard from customers as they navigated the unprecedented jump to online shopping as brick-and-mortar retailers shut their doors. At the same time, they still had to plan for regular calendar events like Black Friday/Cyber Monday and product launches. We announced BigQuery Flex Slots to help them scale their cloud data warehouses up and down quickly while only paying for what they consumed. We also made it easier to optimize data processing and migration to the cloud with a new Dataflow change data capture (CDC) solution that focuses on ingesting and processing changed records, rather than all available data.
In addition, we recognize that organizations are dealing with an increasing number of rich assets to meet the demands of a data-driven workforce. Data is now used by everyone in an organization—not just data analysts. To us, that means giving people smart tools to derive more value regardless of their roles, such as a data catalog for self-service data discovery or product recommendation reference patterns that make it easier to use data to improve customer experience.
Making data analytics work for you
Despite its challenges, 2020 was also a year of unimaginable growth, innovation, and inspiration. At Google Cloud, we learned a lot about what’s important to you and how you’re using data analytics to reach new milestones.
We heard stories from KeyBank and Trendyol Group as they migrated to BigQuery cloud data warehouse, learned how Procter & Gamble uses cloud analytics to personalize their consumer experience, and helped ThetaLabs partner with NASA to deliver more engaging streaming video.
Major League Baseball (MLB) used Google Cloud to derive better insights from baseball data that helps broadcasters and content generators tell better stories and drive fan engagement. Conrad Electric selected Looker to gain visibility into product performance and unlock insights to optimize them accordingly. And Blue Apron embedded smart analytics across the entire customer journey, from recipe recommendations and improving the quality of their supply chain to streamlining packaging workflows.
But perhaps the most inspiring leaps have been the ways smart analytics can be leveraged to help in the face of crisis. For instance, Commonwealth Care Alliance (CCA) used data analytics from Google Cloud to help clinicians and care managers prioritize care for high-risk patients. Reliable data and an easy way to get answers has made it possible for them to keep pace with changing factors and ensure they could provide the best care for their members.
Get ready for 2021
Google Cloud data analytics training for all skill levels gives you the confidence to build a data cloud and take advantage of our open, flexible, and intelligent platform. Learn more about our smart analytics solutions at Google Cloud.
On behalf of Google, we’d like to thank you for being on this journey with us. We wish you the warmest of holiday seasons and can’t wait to see what we’ll build together in 2021.
Gartner, Magic Quadrant for Cloud Database Management Systems, November 23, 2020, Donald Feinberg, Adam Ronthal, Merv Adrian, Henry Cook, Rick Greenwald
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