Data’s innate diversity is both the key to its value and its most challenging aspect. Unifying diverse data can lead to confident decision making, yet data fragmentation and a lack of data freshness impede enterprise success.
Experts from Korem joined DBTA’s webinar, Turning Disconnected Data into Business Intelligence, to explore how, through a graph-based API architecture and the flexibility of GraphQL, enterprises can achieve true data integrity that fuels decision making with clean, interconnected, fresh datasets.
Amaury Charpentier, marketing, Korem, contextualized this conversation with the pressing business questions that need fast, accurate answers. These questions “are common to every single project, no matter what industry you’re in, that need to be solved no matter what,” explained Charpentier, which include:
- “Where can I find new customers and understand areas eligible for funding?”
- “Where should I invest to get in a market first and maximize the return?”
- “Which products are in demand and should be deployed first?”
- “How do I make sure I meet statutory requirements in the area?”
- “How can I streamline my deployment workflow and limit and optimize on-site intervention?
“Even just a few percent of inaccuracy in your answer to any of these questions can have a huge impact on your ROI,” said Charpentier. “The common, key element between all of these questions is that they can—and most importantly, should—be answered with data.”
Charpentier further emphasized that this data is not just valuable for its volume; it must be “diverse, high-quality, and…connected data.” Regardless of the decision being made within a business, most likely, it will require cross-domain data that is defined by its reflection of the real world—a vastly interconnected, nuanced space.
Yet, with more diverse data, and therefore more data sources, more challenges arise. Demands for context-rich, real-time data with entity-level intelligence encounter common obstacles in terms of data integration: fragmented datasets, rigid ETL pipelines, and static data files.
Amine Kriaa, solutions architect, Korem, then introduced the Precisely Data Graph API, a solution that serves as a centralized access point for a vast array of datasets—streamlining the way we interact with data. This API enables users to enhance the depth, completeness, and power of their data underscored by a flexible, ease-centered framework for data enrichment.
What enables the Data Graph API is GraphQL, a declarative query language for APIs that drives a flexible, efficient way to request data. Compared to traditional APIs, GraphQL enables:
- Faster time-to-value by reducing development effort, enabling teams to fetch only what’s needed and therefore accelerating feature delivery
- Improved customer experience by enabling faster and more responsive applications, achieved through optimizing data retrieval and unnecessary loading times
- Cost efficiency by minimizing backend processing and API calls, lowering infrastructure costs compared to REST and SOAP
- Flexibility and adaptability that allows businesses to evolve their APIs without breaking existing clients
Ultimately, the business advantages of the Data Graph API range from a low barrier of entry to simplicity in demonstrating value, more flexible analysis and synergy, and faster decision making.
This is only a snippet of the full Turning Disconnected Data into Business Intelligence webinar. For the full webinar, featuring more detailed explanations, a Q&A, and more, you can view an archived version of the webinar here.