Data is clearly becoming the next currency in the world of business and enables organizations to do so much more than they could in previous decades. Today, data is not only the perk of tech companies, all walks of industries can leverage their processes, softwares, machines and more to collect valuable data about their operations. But data and how to extract valuable insights from it can be overwhelming for most.
Businesses are looking to accelerate their growth by drilling down into their data and establish a “data-driven” approach to their daily decisions and long term strategies.
The foundation of this approach starts by laying down the correct data platform for your entire organization to align their tools and augment their capabilities by using cross-functional data sets.
Before we jump into what businesses get out of data platforms, let’s get our semantics in line: A Data Warehouse is not a Data Platform.
A data warehouse is a medium of storage and processing for data engineering experts to build their queries, store their results and manage ingestion. Any automation will require engineers to build tedious custom processes in order for operations to run as you’d expect.
On the other hand, data platforms are feature-rich environments for all data contributors and users. They usually combine a wide variety of functionalities of data lake, data warehouse, data hub and elements of BI tools that allow low-code data pipeline building and out-of-the-box connectors, easily configured with no expertise required. These types of platforms relieve the burden on data teams while increasing the reliability and scalability of the infrastructure behind the scenes.
As you can understand, modern data platforms do so much more than a simple warehouse. The benefits of putting in place a cloud data platform are great in numbers, let’s unravel a couple of them together.
Your Data North * (Star)
Think of a data platform as the ultimate reference library for your business data. Every department, be it marketing, sales, finance, or operations, can rely on their platform to obtain accurate, up-to-date information. When each department operates from this shared “library”, it ensures consistency in insights and strategy across the board. When everyone knows where to go for their data needs, the benefit is twofold: it eliminates potential discrepancies arising from varied data sources being understood or defined differently and bolsters overall productivity as teams can confidently lean on this single source for all their data needs.
Unified Data Sources
At its core, a data platform serves as a convergence point for diverse data points. Instead of grappling with disparate datasets scattered across different apps and warehouses, stakeholders gain access to a singular, consistent source. This centralization is pivotal. When data speaks a unified language, it allows for clearer insights and empowers businesses to make decisions that are both timely and precise. No longer are data teams spending precious hours on data reconciliation; instead, they’re deriving actionable insights from comprehensive and harmonized data.
Silos No More
Let’s face it, you can have the best tools and softwares in place in your organization but employees will use whatever they want to use when it comes down to the nitty gritty of their day-to-day tasks. These unofficial SaaS softwares and tools, also known as shadow IT, can be embraced as long as they don’t remain segregated silos and can be consolidated. Data silos, historically, have been a bane for comprehensive data analysis and often results in fragmented views, hindering your ability to extract meaningful insights. A data platform directly addresses this challenge.
By centralizing data storage and access, it effectively reduces, if not eliminates, data silos. This means businesses can view their data holistically, allowing for a broader and more in-depth analysis without impacting the users’ workflow. The ripple effect is seen in increased efficiency and a marked improvement in the quality of your insights.
Complex Queries, Faster Results
One of the standout features of a data platform is its robust architecture tailored for complex queries. In a world where the speed of insights can be the linchpin for competitive advantage, data platform excel. Their specialized design significantly enhances query performance, cutting down the time it takes for businesses to extract actionable insights from their data. This ability to quickly respond to intricate questions empowers businesses to make informed decisions swiftly, offering them a crucial edge in today’s fast-paced market landscape.
Historical Data Analysis
Data platforms also serve as an expansive repository for historical data, turning them into time machines of sorts for businesses. This isn’t just about nostalgia; it’s about the power to forecast and strategize. Companies can dig deep into historical data to identify long-term trends, seasonality, and patterns. Such historical perspective provides a sturdy platform for predictive analysis, enabling businesses to make forecasts with a high degree of confidence. In essence, a data platform doesn’t just tell you where you’ve been, but helps you discern where you’re going.
Automated Data Workloads
The functionality of a data platform extends beyond storage and analysis to include automation of routine data tasks. Let’s face it, your skilled data analysts can contribute far more to strategic projects than they can by spending their mornings refreshing Power BI dashboards. Automation within a data platform can handle these repetitive tasks, freeing up human resources to engage in more value-added activities. This not only boosts productivity but also allows your data teams to focus on strategic analysis and decision-making, truly leveraging their expertise.
Data Cleaning & Transformation
Fragmented and inconsistent data often undermines the analytics pipeline, leading to skewed insights. Data platforms alleviate this bottleneck by acting as a refining furnace, subjecting incoming data to a stringent process of cleansing and normalization. This ensures that the data within the platform is not just voluminous but also homogenized, setting the stage for uniform and reliable analyses.
Data Testing
Beyond just storing information, modern data platforms incorporate rigorous validation protocols to confirm the integrity and quality of the data. From schema validation to boundary tests, these procedures make certain that your data adheres to organizational standards and is fit for your specific use-cases. This quality assurance aspect of data platforms adds an additional layer of reliability, ensuring that your analytics are based on solid, trustworthy data.
Higher Accuracy
The beauty of a data platform lies in its capability to enhance the precision of analytics. When data is both standardized and stringently tested, it culminates in a resource that’s highly reliable. With fewer inconsistencies to worry about, the insights derived are not just coherent but also remarkably precise. This sharpens the decision-making process, allowing businesses to operate from a vantage point of data clarity and accuracy.
The Earlier, The Better
Imagine laying the foundation stone of a colossal tower, one that grows taller with every layer of bricks (or in this case, data) added. Leaving your data team or business analysts scrambling to rebuild every query for each request they get is the equivalent of playing Jenga instead of a sturdy structure and quality models. A data platform offers just that — a data infrastructure. As the chapters of your company’s growth story unfold, this structure stands strong, ready to accommodate, and evolve based on your needs.
Scalability is a key concern for any growing business, your data storage requirements will undoubtedly expand. A data platform can gracefully accommodate this increased volume, scaling alongside your business. Importantly, this scaling doesn’t come at the cost of performance. Whether you’re managing gigabytes or petabytes of data, a data platform maintains its efficiency and speed, ensuring that your business’s data capabilities grow in tandem with your ambitions.
As your data teams build on this ever-growing structure, it becomes clear that your data-driven projects not only find their footing but also deliver an enhanced ROI in a fraction of the time that typical just-in-time requests making the investment in your data platform well worth its petabytes in gold and strategic foresight.
Today’s modern businesses need every advantage they can get to rise above their competition. By investing in a cloud data platform, companies aren’t just buying a storage solution; they’re procuring a powerful tool that propels informed decision-making, unlocks the door to automate operations, and can even ready their business to AI projects.
Tackling The Data Problem Head First
Our team caught on to this problem and built BEEM, a platform that enables companies to skip the building process and dive right into the value creation aspect of owning a cloud data platform. We consider that every company shouldn’t have to hire a full team of software engineers, data engineers, cloud infrastructure engineers, and more, to build the core components which make up today’s modern data stack to achieve the same result. We offer a fully managed cloud data platform so that data teams can become fully autonomous in the connecting data sources, modelling data in SQL and even syncing datasets into other tools using our reverse ETL flows.
At BEEM, we believe that a true cloud data platform should be a collaborative space for business users and data teams alike. We’ve built the fundamentals for every organization to democratize self-serve access to data, all the while relying on strong access management and governance. Sign up for a demo learn more about BEEM!
I’d love to hear you! Have you recently moved your organization data onto a modern data platform or data warehouse? How did that go for you?
