Philip Miller, Customer Success Manager at Progress, explains how a data platform approach can enable business agility.
The wave of digital transformation has brought innovation and productivity to all industries, yet there’s a serious challenge – to derive business value from vast amounts of real-time data stored across various business systems and functions.
Traditional database technologies storing only structured SQL data are simply unable to adapt to new forms of unstructured data such as documents, graphs, geospatial data, etc. This becomes a major barrier to creating integrated user experiences and optimising outcomes. To address this, a modern trending approach called data agility is needed, allowing the integration of facts and contextualising information for different business users.
To be able to move with the evolving business landscape means taking a modern approach to connecting, creating, interpreting and consuming data. This allows leaders to make simple, powerful changes to how information is interpreted and acted upon, which can reduce time to value and achieve transformative outcomes. The goal of which is to have raw data transformed into valuable and connected, augmented with human-intelligence at scale.
Data agility is purely measured by the speed and flexibility at which an organisation can meet goals swiftly and at scale, regardless of whether it has a hybrid or multi-cloud infrastructure. Understanding the metadata from these forms is critical to enable organisations’ data analysts to extract and work with the overall data set. Therefore, achieving true data agility requires a data platform capable of delivering this flexibility and scalability, a semantic data platform that can connect active metadata and operational data, active metadata and active meaning.
The shift to agile data platforms
The traditional data management approach typically involves using disparate database and data management tools, knowledge models and rule engines. This fragmented approach can be rigid and inflexible, requiring extensive modifications to applications and systems to accommodate new requirements. Modern businesses need the freedom to leverage new tools and seize emerging opportunities quickly and effectively. Waiting months to implement and reap the rewards of a new tool can mean missed opportunities and loss of competitive advantage.
In contrast, a data platform approach can dictate business survival and success. Firstly, the ideal data platform should be capable of consuming structured, semi-structured or unstructured data. This agile data platform should also accommodate diverse data models, whether traditional structured query language (SQL), resource description framework (RDF), geospatial or temporal. It will apply human intelligence at a machine scale and enrich data with metadata and apply ontologies and taxonomies.
The best data platform is one that’s tailored to the business’s specific needs and ensures first class security and governance. This flexibility and security of a data platform is even more important to handle large-scale operations in the context of the rapid advancement of data-related tools, including AI and language models like LLMs.
The benefits of a semantic data platform
The organisation will have various data platforms, perhaps in the form of a CRM, an ERP or an on-premises solution, but joining the dots to extract real-world insights from this (exponentially growing) data is a huge challenge.
The solution, a semantic data platform, can turn raw data into actionable knowledge, meaning that organisations can leverage new data sources and various data types while keeping up with the ever-evolving data landscape. It works such that data, together with its metadata, is collected and introduced into a semantic data platform. Once the semantic data platform ingests the data, it can be classified, enriched, stored tightly coupled with its metadata and put into context. The metadata is effectively the connective tissue between the data and its meaning.
Adopting an agile data platform reduces reliance on IT teams, gives data analytics teams more freedom to do their jobs and drives synergy between an organisation’s IT efforts and its business goals. It also allows IT professionals to work with their organisation’s data in a more flexible environment, which allows them to gain better visibility into their infrastructure environments. In turn, data analysts can then provide stakeholders with business insight.
Once deployed, an agile data platform can reduce time to market for specific projects. It can give IT and analyst teams easy access to shared data which can boost team productivity. Most importantly, there are significant cost savings since its implementation doesn’t require a full infrastructure overhaul for further investing in additional data tools.
First steps towards data agility
As with all transformational initiatives, a data agility platform integration requires some considerations to ensure success. The best ways to get started are to:
- Identify the business problem that data agility can solve. With data challenges everywhere, it’s important to identify the places where the organisation is most struggling with data. This means clearly understanding the problem, the dependencies (people, process, technology), and successful business outcomes that solving it will generate.
- Choose the right technology. This means carefully assessing the use case to decide what technology is the best fit. Industry analyst reports, such as the Gartner Cloud DBMS Magic Quadrant, offer provide comprehensive analysis of suitable solutions.
- Get C-suite buy-in. A strong business case that clearly outlines the rationale for the project is essential, along with measurable goals and tactics is essential to gain the right buy-in from internal stakeholders. The next stage is to take this to a proof of concept that will illustrate how this technology can deliver transformational outcomes.
Data agility steers business to success
A singular, integrated data platform frees businesses from the constraints of patchwork solutions and empowers them to respond quickly to market changes, consumer demands and emerging opportunities. This data platform must be able to adapt to diverse data forms, support varied data models, and enrich data with metadata for driving valuable insights.
By deploying a semantic data platform, organisations can effectively convert their spiralling amounts of data into actionable insights, create value for customers and forge a resilient path to success. Unlocking the true potential of data can fuel growth and steer the business to a prosperous and sustainable future.
Final thoughts
One quote that became popular early in this digital transformation age is that “Data is the new oil.” That it is, and will become even more so – the most important asset to businesses and organisations worldwide. Just as unrefined oil straight from the source has very few practical uses, it must be refined into new forms to extract the real value. The same goes for data.
Modern businesses need to turn data into information, harmonised, curated and contextualised information that is machine interpretable with human intelligence applied to it. Only then will they extract the value and insights in that data to drive agile change and innovation in the business. An agile, scalable and secure semantically enriched data platform is the facilitator for true business agility.
