Modern Data Stack

Data Warehouse Architecture

Switching to a data warehouse architecture offers a solution for organizations facing slow performance, limited usage, and scattered data sources. By consolidating data into a unified location, it provides faster processing, increased usage frequency, and comprehensive analysis. Benefits include autoscaling, visual SQL workflows, a centralized catalog, cost optimization, time savings, and improved collaboration. Acting now ensures timely access to insights and better decision-making.

Why Customers Consider a Data Warehouse Architecture

Their current warehouse is too slow for their needs.

The data warehouse is only used a couple of times per day. 

Too many data sources, and need them to be all in one place.

Data Warehouse Architecture
Data Integration

Source to Cloud Data Warehouse

Loading valuable business data into your cloud data environment is the first step.

Transforming this data in the cloud to unlock hidden insights within your business is the second step. 

In this technology stack, we use Matillion to do both. 

Data Storage and Processing

Cloud Data Warehouse to BI

Snowflake is a SQL data warehouse that has flexibility to handle inconsistent workloads while maintaining predictable performance.  

The fully managed, autoscaling warehouse isolates compute resources based on use case, including ELT, ad-hoc querying, and live analytics. This isolation reduces interference and allows companies to right-size their performance to achieve their desired SLAs and cost forecast.

It also allows for more lightweight ETL tools that leverage SQL pushdown and query-based analytics tools that visualize real-time data.

Data Analysis
Data Analysis

BI to Insights

The upstream data transformations meticulously refine and structure your data to seamlessly integrate with the most advanced data analytics tools on the market, such as Tableau, ThoughtSpot, Power BI, and a variety of others. With our advanced data solutions and tailored transformations, your data will be optimized for in-depth analysis and visualization, empowering you to uncover valuable insights and make informed decisions with ease.

Data Governance 1
Data Governance

Insights to Answers

Most data catalog software focuses on metadata management and governance. Important as those capabilities are, they don’t address the full scope of what an enterprise data catalog can and should do. Built on an enterprise knowledge graph and data virtualization platform, delivers powerful search and discovery capabilities along with self-service analytics and collaboration, so your entire workforce can be data-enabled. The catalog-as-a-service platform makes it easy for IT and business users to get more from data.