Modern Data Architecture
We deliver solutions for Fortune 1000 clients across a wide spectrum of industries and fully utilize data and advanced analytics to transform their business
Get serious about your return on data investment
Everywhere you turn, it’s data this, analytics that. The use cases are vast, the promises endless: “It’s the wave of the future, everyone is doing it, and it will generate money, money, money.” Yet we see companies spend tens of millions, or even hundreds of millions of dollars, on traditional data and analytic solutions that fail to live up to expectations. The bottom line is this: companies invest in the wrong data technologies, build solutions in a vacuum, and struggle with how to apply data and analytics to generate business value.
Why Clarity’s Modern Data Architecture?
This is what we do. We have the power to ingest your data from across your organization, store it in a data lake, call upon it whenever needed, and integrate powerful applications to create a seamless and comprehensive platform. We reduce development time from years to months, decrease delivery costs by up to 50%, and generate ROI through revenue generation and operational efficiencies.
Modern data architecture consists of:
Initial assessment and blueprint - We will evaluate your current technology stack and work with your IT leaders to determine the best data architecture solution.
Strategy and delivery roadmap - We have a proven methodology to evaluate both business and technical requirements, provide resource and cost estimates, and translate your inputs into an actionable roadmap to implement the solution.
End-to-end implementation - We like to say our Delivery Roadmap is so good that any company can execute it on their own, but we know most companies don’t have our years of experience or expertise. We’re ready to deliver an end-to-end architecture and technical solution.
Post-production support - We know the work doesn’t stop when the project is implemented; we are prepared to help augment your staff with post-production support.
We make an important distinction between “infrastructure component" and "capabilities enabled." We know the technical capabilities that companies want enabled and have developed accelerators to seamlessly integrate and deliver the right infrastructure components.
Data ingestion framework Parameterized sourcing enables the loading of data from supported source systems into the data lake using a metadata-driven application to automate development tasks.
Data transformation framework For batch and real-time streaming, we have ETL solutions to transform raw source data into forms that can be used by downstream processes.
Data virtualization We provide a common data access layer across the data lake, analytics laboratory, and EDW. A common access layer allows authentication to be centrally managed and provides a homogeneous view of disparate data sources.
End-to-end platform delivery We move data through a common, tiered approach. Data is moved from source systems through an ingestion layer and into a data lake. From there, it will be prepared ahead of offload into an EDW layer. Multiple solutions, or "applications," will leverage the data in the lake and the EDW.
Rip and replace Replace highly expensive EDW platforms, such as Teradata or Netezza, into cloud-based data warehouses like Snowflake and Redshift.
Augment your data warehouse Leverage data lakes to stage, process and archive all your EDW platform data, and offload ad-hoc queries and analytics into the data lake. Augmenting your data warehouse allows you to free up resources from expensive platforms.
Teradata replacement Companies are trying to replace Teradata with Hadoop technologies and failing miserably. While Hadoop can augment Teradata, it cannot replace it to the point where a company can expect equivalent or better performance.
We have better cloud data warehouse options if you want an alternative to Teradata. We have proven with previous clients an improvement in end-user query performance by a factor of four times, along with a reduction in cost by at least 50%. Our clients find that the improvement in query performance drives substantial business benefits through system efficiencies and productivity gains by knowledge workers.
“Dance like no one’s watching. Email like it will be printed on the front page of the New York Times.” Cheeky quote, but let’s take it one step further… create business data like it’s going to be
The analysis and management of data from multiple sources may introduce issues of trust, quality control and stewardship. If you want to study someone else’s data, can you trust that it’s accurate?
Another day, another data management metaphor... Gartner, for example, cited the “data fabric” as one of their “Top 10 Data and Analytics Technology Trends That Will Change Your Business.” The term