Written by Roman Stanek |
Companies need a new approach to data management — one that goes beyond data visualization and unlocks the transformational power of fully functional data and high-integrity insights. As many enterprise software solutions have moved to the cloud and are delivered “as a service,” it’s time for data to be treated the same.
Businesses that embrace and implement Data as a Service (DaaS) transform their data. They make it the foundation of all of their business decisions. They leverage data at scale to fuel growth and market leadership. GoodData is a DaaS company. And we believe that the best DaaS companies adhere to these foundational principles.
Pillar 1: We believe that every business decision should be a data-driven decision.
DaaS provides a platform to incorporate data into every business decision — strategic, tactical, local, global — by delivering accessible insights to multiple departments within a company.
A unified data value chain can serve as a focal point for all processes and decisions. It encourages a shift from single use-cases (“I need a report pulled to update slides for the board meeting”) to comprehensive business intelligence (“I need to understand all aspects of my customer’s buyer journey”).
Pillar 2: We believe that Data as a Service is the next frontier in cloud infrastructure.
The cloud has ushered in a modernization wave for data storage. But how do you access data stored in lakes and warehouses? How do you make sure the right internal and external users have access to the data pipeline?
DaaS is the way to provide real-time, scalable, global insights and analytics both inside and outside of a company — and cloud infrastructure enables it. The most innovative businesses have the infrastructure to deliver insights better, faster, and at a reasonable cost to whoever needs access.
Different cloud services will be better suited to different parts of an organization. If you are using a multi-cloud strategy, an analytics engine that can process data from various cloud origins can help produce robust views of your data.
Pillar 3: We believe that data literacy shouldn’t require a data science background.
Decisions are made across all parts of a business. In order for analytics to be truly transformational, every user must have access to data in a format they understand.
It can be tempting to consider data literacy as a data scientist’s responsibility to translate for the uninitiated. Of course, technical teams should still know how to understand data — but not everyone at an organization needs to be able to interpret formulas based on a .CSV file. If your data provider is presenting the data in a simple way with accessible storytelling, anyone at a business can tap into its power.
Data literacy should not be a barrier to data-based decisions. Companies can set their teams up for success by providing better-designed, data-driven applications. With complexity removed so that data is delivered as an intuitive asset, it’s much easier to interpret — and act upon.
Pillar 4: We believe in rendering data in simple business terms.
In the past, business leaders would have to rely on IT departments to pull data reports. If the IT department defined a term like “customer” or “profit” differently from the C-suite, that data was essentially rendered irrelevant.
An effective semantic layer that translates data into recognizable business terminology provides the framework for unifying insights at all levels of a company. And establishing data governance — guardrails around organizing and utilizing data — ensures information is consistent for all users. And data consistency builds trust, fosters collaboration and ultimately drives value from the data's insights.
Pillar 5: We believe that a commitment to data starts with leadership.
Across business operations, lack of strategy leads to lack of investment, which leads to lack of return — which dries up support for future investment. A successful data strategy requires building the support systems and solutions it needs to work efficiently and effectively. The more a company invests in data — with both capital and culture — the easier it can be to turn data from a cost center into a revenue generator.
The most successful, innovative companies — like Netflix or StitchFix, to name a few — are managing increasing amounts of data to gain an edge. Data should be seen as something that can empower teams. And harnessing the power of Data as a Service can lead to more meaningful returns.
Written by Roman Stanek |