Integrating Data Warehouses into Front-End Apps
Data warehouses represent an essential part of virtually every organization's analytics efforts. These resources have evolved significantly over the past few years, improving in terms of usability, capacity and more. Among the most important developments in the field has been the rise of document-based data warehouses. These data warehouses offer major advantages - most notably, the potential to produce more robust, informative analytics insight.
However, document-based data warehouses also present a number of challenges. One key example: How can you integrate these data warehouses into front-end applications? To achieve this goal, developers need to focus first on the desired outcome, then consider the best tools for reaching that level and form of integration.
Understanding the goals
Document-based data warehouses are so valuable because of the context they can provide to analytics efforts. Typical data warehouses are only applied to structured data. While this can undoubtedly prove extremely useful, it is also limiting, especially when it comes to understanding data trends and developments over time. To gain this greater understanding, context is essential, and yet this context is often described in text-rich documents, which traditional data warehouses cannot utilize. A document-based data warehouse overcomes this hurdle, producing much more robust analytics insight.
For this insight to prove valuable, though, it needs to be readily available to end users. As 1 Key Data emphasized, that requires a focus on visualization.
"Usability is arguably the most important end goal, but it is not the only one."
"Regardless of the strength of the OLAP engine and the integrity of the data, if the users cannot visualize the reports, the data warehouse brings zero value to them," the source wrote. "Hence front-end development is an important part of a data warehousing initiative."
Usability is arguably the most important end goal in this area, but it is not the only one. Developers must also keep in mind the importance of consistency, speed, capacity and security as they pursue front-end integration with their document-based data warehouses. Consistency is critical, as every user who accesses the warehouse should have the same experience and see the same insight. If this is not the case, the entire endeavor will prove suboptimal.
Additionally, it's imperative that users can access the insight quickly enough to perform their jobs. If the integration effort does not prioritize speed, this won't be the case.
Capacity is related, but worth considering in its own right. Data warehouses will only grow over time as more information becomes available. The integration strategy needs to take this into account.
Finally, it's absolutely essential that the information remains secure as it travels from the data warehouse to the front end.
With these goals in mind, there are a number of options available for achieving integration. In terms of development and deployment, 1 Key Data noted that a lot of organizations rely on scripting languages such as ASP, PHP or Perl. Alternatively, some firms turn to off-the-shelf products. Still others look for OLAP vendors that provide their own front-end integration solutions.
The right approach will vary.
Ultimately, there is no best answer here - each organization will have its own document-based data warehouse with its own integration challenges and requirements. A key, overriding point, however, is to look for an approach that can offer a high level of customization. Not only is this crucial for the immediate goal of achieving front-end integration, but it also ensures that integration does not become an issue in the future as the company and its data-gathering and analytics efforts evolve.
Tackling this challenge in the best possible manner can be difficult. That's why it's often ideal for companies to turn to third-party enterprise application integration experts to maximize results while minimizing costs and risk.