Due to its diverse history of solving data-related challenges across different industries, Raybeam understands the viewpoints of various departments of an organization. When big data began influencing how advertising and marketing teams collected data, Raybeam recognized that marketing and data architecture go hand-in-hand. The company predominantly served advertising and marketing organizations from 2008 through 2015. In recent years, however, Raybeam has helped clients in retail, healthcare, insurance, and finance, too. “We see that a data-driven and data-aware mentality is permeating every layer of the organization. For example, there’s now an expectation that product and customer service be able to justify their decisions, and data can help with that. As the need for data increases, we can step in and solve problems across industries,” stresses Briski, noting that Raybeam addresses issues “not from an engineering perspective but a business-wide perspective.”
Some of the data-related challenges that Briski is referring to are focused on governance and security around data. With EU’s GDPR and the soon-to-be-implemented CCPA putting stringent restrictions on how companies collect and use data, Raybeam’s clients rely on the data integration vendor to translate what the laws mean in their use cases and implement solutions in a way that follows the law. Starting with the belief that an ideal data architecture “is where it’s simple to do the right thing,” Raybeam ensures its clients are not only compliant with existing laws but also remain futureproof for the emerging regulations. “When we build out a data system, we focus on governance right from the beginning. This way, when additional laws come into effect, the new monitoring and security protocols can be integrated into the platform,” explains Briski.
Raybeam’s BI and analytics projects are just as pivotal. By layering analytics and machine learning atop its data warehousing solutions, Raybeam strives to shorten the duration it takes clients to progress from “insight to experimentation, and finally implementation.” Briski informs, “Time-to-insight is a key metric in developing analytical solutions. This quick pace helps a client to experiment with the insights before socializing them across the company.” Quicker iterations on top of solid experiments help companies develop an engine that can drive innovation across the entire enterprise.
Time-to-insight is a key component of our analytical solutions
Looking ahead, Raybeam will continue to take a “business-first approach” to solving data integration issues for its clients, looking at the business first and the tooling second. With over 25 years of experience in data warehousing—beginning with involvement in the early search engines—Raybeam possesses the deep technological expertise to address both existing and forthcoming trends in the marketplace. Trends that Raybeam is closely monitoring include explosion of metadata coupled with modern ML/AI techniques, IoT data storage and processing, and the rise of data governance as a driver of strategy. Also, as mentioned before, Raybeam isn’t averse to SaaS services and managed service providers bolstering its solution offerings. “While some may feel managed services are taking business away from us, it’s actually the opposite. Now, we can do custom work atop the foundations laid out by these vendors, allowing us to get to a successful outcome more quickly,” concludes Briski. “Managed services make the time-to-insight of a Raybeam solution even faster.”