Moving data to the cloud is about democratizing data. But democratization is about utility as well as access.
When it comes to storing data, the cloud is the place to be. By the end of this year, over half of all enterprise data will be hosted on the cloud, along with two-thirds of all business data generated and processed by SMBs. The pandemic-inspired shift to remote working will only accelerate that transformation; in fact, around 90% of businesses say they’ve increased their use of cloud-based data storage during the COVID-19 crisis.
If you’re one of those businesses, congratulations. You’re embracing a trend that’s reshaping the business world and making it easier to ensure seamless and scalable data access across a wide range of devices and geographies. With cloud-based storage now more secure and reliable than ever, there’s never been a better time to move data online and harness the flexibility, cost advantages, and futureproofing offered by cloud technologies.
But don’t start slapping yourself on the back just yet. It is only the first part of the problem. Data doesn’t have value until you put it to work – so in addition to putting your data on the cloud, you also need to make sure you can use it effectively once it’s there.
Dropping the ball
Unfortunately, that’s where many organizations are still dropping the ball. Both large and small businesses are using cloud storage to consolidate and store their data, but they’re failing to use corresponding cloud-based tools and analytics to unlock the power of that data across all their organizational workflows and customer touchpoints.
While modern businesses increasingly rely on the cloud, the reality is that most enterprise analytics other than CRM are still being handled on-premises. As recently as five years ago, less than 7% of data analytics were handled using cloud systems; in 2020, around 30% of analytics took place in the cloud. That’s an improvement, but it still leaves a vast amount of actual work being done using outdated on-premises systems.
Moving all your data to the cloud and then using on-premises technology to interact with and process it is like installing gigabit Wi-Fi in your office and then using it to fax handwritten notes back and forth to your clients and direct reports. You might be able to run a business that way – but you’ll be able to run your business better if you upgrade your entire operational chain to take full advantage of the technologies in which you’re already investing.
Moving analytics to the cloud – the place where your data already lives – lets you move faster, fuel innovation, and create value for customers. Instead of clunky first-generation business intelligence (BI) tools, you can transition to lighter, nimbler, and lower-cost solutions that can be maintained without the need for costly oversight from technicians and engineers. That frees up dev teams to focus on work that delivers real value, making the adoption of cloud tools a key differentiator for your organization.
The rise of cloud-based data warehousing
The shift to cloud-based analytics has been enabled by innovations in the field of data warehousing, which now make it far more feasible to use cloud data to drive effective decision-making across entire organizations. With properly formatted and organized data, accessed using SQL without the need to move data around, it’s become easier than ever to obtain and analyze cloud-stored data in fast, efficient, and cost-effective ways.
Of course, you can run a data warehouse on-site, too. But cloud-based data architecture is inherently scalable: if your business grows and the volume of data you’re handling surges, your cloud warehousing capabilities will always be able to keep up. By contrast, on-premises data warehousing can be tough to scale up effectively. All too often, data systems that worked for a small, scrappy business aren’t suited to a company that’s grown to ten or 100 times the size – and rebuilding your data tools as you grow is like rebuilding an airplane that’s in flight. You might be able to pull it off, but it’s a risky, expensive, and inherently unstable way to run a growing business.
Because cloud-based data warehousing is now a mature, proven technology, on the other hand, it’s easy for growing organizations to access and utilize their data at scale, drawing on popular tools including Amazon Redshift, Microsoft Azure SQL Data Warehouse, Snowflake, and Google BigQuery. Such solutions make it even easier and cheaper for organizations to deploy sophisticated data-warehousing strategies, bringing cloud analytics within reach for companies of any size.
Still, structured data warehouses are of little value unless they can be interrogated, mined, and turned into actionable insights. For too long, that’s been the exclusive province of experts and data scientists. But because cloud analytics can, in principle, be accessed from anywhere by anyone using your products, they make it possible to democratize data and bring actionable intelligence within reach of everyone who can benefit from it.
That requires a new approach to analytics, using data storytelling and visualizations to interpret data and deliver useful insights to end-users who may not be especially data-savvy or who don’t have the time or inclination to go digging through endless spreadsheets and tables. When hosted, such approaches can bring data and analytics into your team’s workflows, helping people at all levels of your organization to make smarter decisions — and they can also integrate into your products, delivering new value for your customers and end-users.
Given the advantages that cloud analytics bring, it’s no surprise that we’re seeing adoption rates growing fast. According to Gartner, two-thirds of data analytics will take place in the cloud by 2024, and with monthly cloud spending now in excess of $1 million for over a third of enterprise organizations, the sector has become a key strategic battleground for companies of all sizes.
The shift to cloud analytics will prove just as transformative as the move to bring data onto the cloud. Companies that anticipate this trend, and move quickly to build out such analytics capabilities, will gain a powerful early-mover advantage as the world’s businesses continue their journey toward fully cloud-based data storage and processing.