Data Management

databricks Partner
Microsoft partner
Snowflake partner

Traditional data architectures and management processes are no longer cutting it to meet modern analytics needs. Digital transformation and the cloud are driving major changes to data management practices and the technology landscape. Potential vendors and tools are growing to a degree that it’s difficult to know the right direction for your organization.

Our team of consultants, data architects, and data engineers have the experience to navigate your journey towards a modern data architecture that drives value for your analytics organization. We help you avoid the hype and implement data warehouses, big data and data lakes that have near-term business value and don’t just implement technology for technology’s sake.

Smartbridge Experience & Services:

  • Enterprise Data Strategy

  • Cloud Data Architecture

  • Cloud Data Warehouse & Data Lake

  • Data Integration

  • Data Quality and Data Governance


Standardized on Microsoft Azure? This eBook will help you establish your Azure data & analytics strategy and roadmap.

Journey to Cloud EBook


Multi-Cloud Cost Control

Multi-Cloud Cost Control – Managing a Multi-Cloud Infrastructure

By the end of 2020, approximately 60% of businesses had moved their work to the cloud with 90% of those companies using multiple providers to support their needs. However, the complexity in monitoring costs of a multi-cloud infrastructure can be disastrous if you don’t take one significant step.


An Overview of Cloud Data Warehouses and Cloud Data Lakes

An Overview of Cloud Data Warehouses and Cloud Data Lakes

The IT environment is constantly changing, but something that has stayed consistent over the years is the need for organizations to perform accurate analysis, create reports and derive results to make critical business decisions.


The Path to Reporting & Analytics: Establishing an Enterprise Data Warehouse

The Path to Reporting & Analytics: Establishing an Enterprise Data Warehouse

A large restaurant chain had many challenges, including: no standard defined for the reports, metrics and business rules; there were too many being produced ad-hoc; more time spend massaging the data than analyzing it.


Each organization is in a different place and has different drivers for data management agility and maturity, but there are some critical capabilities or components that are generally applicable including:

  • Storage & compute flexibility & elastic provisioning
  • Support for parallel & distributed processing
  • Event/data streaming
  • Democratized data access

  • Easy to use without specialized training
  • Ability to handle all data types
  • Business-enabled data engineering
  • Data lab / sandbox
  • Data catalog

Deploying, integrating and managing data and analytics solutions and platforms can be challenging.

Implementing solutions that solve significant business challenges come with a new set of needs and maintenance requirements that sometimes don’t seem like they are properly offsetting the issues they were intended to solve.

If you feel stuck or stretched thin, consider Smartbridge’s data and analytics managed services >

Establish a truly effective analytics organization with your own custom, balanced approach.