As the volume of data continues to grow, data-driven approaches are becoming critical for tech companies and startups across all industries. During our recent conversations with customers, we have learned that managing data and extracting value from it continue to be enormous pain points.
There are a variety of factors causing these challenges, including accessing and storing data, inconsistent tools, compliance concerns, security considerations, and new and evolving data sources and formats.
For example, companies that need to combine data in their legacy systems with new technologies have much to figure out. Should they move all of their data to the cloud? Should the data be in one cloud or distributed across several? How can they extract real value from all the data without creating more silos?
Some companies might be limited to analyzing their data in batches instead of processing it in real-time, adding complexity to their architecture and requiring expensive maintenance to combat latency. Or, they might be struggling with unstructured data, with no scalable way to analyze and manage it. Again and again, the challenges come down to problems accessing data–often exacerbated by silos–and an inability to process or understand the data.
As a certified premiere Google partner, we at Daston are offering companies solutions to this problem. The modern tech stack should be a streaming stack that scales with data, provides real-time analytics, incorporates and understands different types of data, and lets a company use artificial intelligence/machine learning (AI/ML) to predictively derive insights and operationalize processes. These requirements mean that to effectively leverage data assets:
- Data should be unified across the entire company, even across suppliers, partners, and platforms, eliminating organizational and technology silos.
- Unstructured data should be unlocked and leveraged in a company’s analytics strategy.
- The technology stack should be unified and flexible enough to support use cases ranging from analysis of offline data to real-time streaming and application of ML without maintaining multiple bespoke tech stacks.
- The technology stack should be accessible on demand, with support for different platforms, programming languages, tools, and open standards compatible with employees’ existing skill sets.
Daston is helping companies meet these requirements with its expertise in designing and implementing Google Cloud solutions. With these standards met, companies are equipped to maximize their data, whether that means discerning and adapting to changing customer expectations or understanding and optimizing how data engineers and data scientists spend their time.
Would you like to learn more about how Google Cloud can help you get the most out of your data? Contact Daston today for a free consultation.