This article was written by Snowflake and originally appeared on the Snowflake Blog here: https://www.snowflake.com/blog/10-predictions-about-data-cloud-analytics-in-2021/
2021 is the year of the Data Cloud. Powered by the Snowflake platform, the Data Cloud will be the place where organizations across industries can converge to mobilize their data.
Snowflake estimates that there are still hundreds of millions of data sets isolated in cloud data storage and on-premises data centers globally. The Data Cloud eliminates these silos, allowing you to seamlessly unify, analyze, and share your data to reach deeper insights and even open new revenue streams.
As this shift to the Data Cloud takes hold, what data analytics trends will emerge? Snowflake’s team of data analytics experts has 10 predictions about what to expect in 2021 in areas including data science, data engineering, data governance, and data sharing.
Read on to discover the trends that will help you start thinking about how your organization can unlock the value of data faster and more efficiently.
Trend #1: The value of data will rise exponentially
Data—both internal and third-party—has become critical to create insights that help ensure business survival. In 2021, the value of data will become even more important to business success. The key to unlocking data’s value will be the ability to easily unify, integrate, analyze, and share data.
Trend #2: The rise of the Data Cloud
Many IT leaders point to data silos as their biggest challenge to realizing data’s value. The Data Cloud is one unified environment where teams can collaborate on all sorts of data, bringing many different workloads together in a secure, governed manner. The need to copy or move data will become a thing of the past, helping to eliminate many security and governance issues.
Trend #3: Modernization beyond the data warehouse
Achieving a complete view of data requires modernizing not just your technology, but also your processes and workforce. Leading companies will build new approaches to data by creating new roles and responsibilities, enabling organizations to be agile for changing requirements.
Trend #4: Governance continues to be a top concern
As more data is shared and businesses face more privacy regulations, governance must be pervasive. Governance involves knowing your data (understanding and classifying data across your entire ecosystem), unifying security and governance (simplifying governance across workloads with centralized controls), and controlling your data (implementing flexible governance and security policies that don’t hinder innovation).
Trend #5: So long, data lakes/warehouses
Gone are the days when organizations needed to figure out locations and data types for data lakes versus data warehouses, and how to integrate different solutions and systems. Today, a modern data approach enabled by the Data Cloud takes a holistic approach to data, enabling companies to focus on the value of data instead of the logistics of its storage and usage.
Trend #6: Collaboration goes mainstream
It’s very difficult, if not impossible, for disparate teams to collaborate on data. Organizations often have to create copies of databases, or offload data sets, and send them outside of the organization. This creates operational overhead and a massive governance problem, because the second you ship data to a third party, you lose control of it. Companies are increasingly using Snowflake’s Data Cloud and Snowflake Data Marketplace to collaborate on data in virtually any format, at near-unlimited scale, without copying or moving it.
Trend #7: Analytics democratization becomes attainable
Today, organizations are empowering every employee in every department with access to self-service analytics. This is being enabled by easy and governed access to ready-to-use data along with scalable platforms that can handle the workloads, easy-to-use visual analytics tools that can answer questions in near real time, and an increased focus on improving data literacy.
Trend #8: Data processing is available to all
Multiple users can access the same platform to process data for different purposes, including data preparation, data augmentation, feature engineering, and machine learning. As engineers use a more diverse set of languages and tools, data architectures are becoming more complex. The Data Cloud reduces complexity, enabling all users to process data differently according to their needs.
Trend #9: Every app becomes a data app
Today’s applications ingest, process, and encode massive amounts of data, no matter which category they are in. The challenge is to make sure data infrastructures can handle the massive data loads and user expectations for rapid response times. The Data Cloud can support data-intensive applications without the cost and complexity of legacy data systems.
Trend #10: A single platform for data becomes the solution
Companies that want to bring the capabilities of advanced analytics to their employees can take a tool-based approach and perform complex integrations, but this approach becomes labor-intensive and costly. A single platform such as Snowflake enables multiple workloads in one place—including data engineering, data science, data sharing, data applications, data warehousing, and data lakes—helping to unlock value faster and easier.