BI Cost Analysis on data lakes for Your Business
Thanks to the rise of Big Data, businesses now have the power to crunch humongous amounts of data concerned to everything under the sun — from internal operational processes to the industry landscape. And Business Intelligence is essential when it comes to providing real-world intelligence to decision-makers and stakeholders in an understandable format. The intelligence generated by BI forms the basis of organizational-critical decisions taken by those at the side of decision-making. While this understanding is now becoming more robust, however, when doing business, implementation holds more significance than just understanding. And more often the potential impact BI can have on a company, its adoption has been considerably slow across the industry.
One of the core reasons behind a slow adoption rate is the challenges around understanding Business Intelligence implementation due to bad cost-benefit analysis. Delving deeper into the analysis, let’s first have a brief glimpse at what the process looks like and then understand the scope for Business Intelligence cost analysis on data lakes and their respective impact.
Expanding Organizational Analytics capabilities
When looking to expand your organization’s analytics capabilities, the default decision around technology is often: “use more of the same.” However, organizations find that this doesn’t always work, primarily when pursuing digital transformation strategies that entail new types and new data sources. Organizations are now going beyond the default decision to add data lakes to their analytics environments. This shows a significant step forward in adopting modern analytics. Still, they end up capping the potential value of their data lake by continuing to use their existing, traditional BI tools. The rationale behind this configuration is valid — leverage existing investments as much as possible and adopt the latest technologies where much needed. Organizations see the need for a new data platform like the data lake but not the requirement for a new Business Intelligence technology. They try to utilize their existing BI tools to get insights from their data lake. And that is the problem in this situation, in not recognizing that adopting a new BI platform specifically for your data lake is, in fact, necessary.
Once organizations realize that a new data platform requires a new BI solution, one more proof point is needed — cost justification. Indeed, the value a new BI solution creates is the most critical factor, but that’s a meaningful discussion only to IT decision-makers and the business line. Like the procurement department, other teams don’t think about features, capabilities, and processes but instead think about the financial impact. They potentially see “just another BI platform,” which in their minds incurs unnecessary expenditure because they don’t understand the added advantage. It will seem counterintuitive to them that procuring a completely separate BI solution will result in a much low total cost of ownership. In contrast, they likely agree to data lake procurement because of the obvious up-front economic advantages with respect to software and hardware licensing, but proving the cost advantage of a new BI tool requires a little more effort. Fortunately, the cost analysis is straightforward when considering BI technologies that are native to data lakes, like Arcadia Data, since the associated workflow is significantly more efficient than the workflows required with traditional BI tools used on data lakes.
For instance, a model for analyzing the costs of a new Business Intelligence solution designed for data lakes Vs a traditional Business Intelligence solution designed for DWs entails assessing the steps in the analytic journey. Each step needs HRs, described as full-time equivalents (FTE). So with a Business Intelligence solution native to data lakes, you can eliminate a few common steps in the data warehouse world, but unnecessary in a data lake world. One clear benefit of data lake BI solutions is analyzing data lakes without any data movement. There’s no requirement to move data to a dedicated BI server, which traditional BI tools require to provide the performance needed by end-users in a production environment. There’s no redundant administrative effort around data modeling and security with no data movement, which frees up FTEs for other business-critical activities.
Final Thoughts
According to Gartner’s prediction, the Business Intelligence market is expected to grow to US$22.8 Billion by 2020. And, in line with the current business landscape, the time had never been more apt to invest in BI solutions; however, doing a proper cost analysis is the key to making the right pick for your business. At Polestar Solutions, our Business Intelligence (BI) Services encompass data management (with Data warehousing & Data Lake), BI Consulting, diagnostics of existing analytics setup, data visualization & reporting, and adoption enhancements with innovative enablers, end-user training, and extensions. Polestar will assist your business make better decisions by providing expert-level business intelligence services.
