Data platforms and analytics

A well-functioning data environment means greater visibility and a clearer path to digital transformation. Build a high-value data ecosystem with holistic expertise and a strategic approach from Insight.

Data ecosystems that work

In years past, sophisticated data environments weren’t necessary for most businesses. It was simple to organize, store, and protect data. The important data was easy to find, and analysis was performed manually by higher-ups looking for specific points.

Today, modern data platforms and robust data analysis capabilities have become mission critical as data volumes and IT environments expand. Advance your approach with Insight. With expert guidance adopting modern architectures and solutions, we’ll help you:

Eliminate data silos by adopting a unified data service that is open, reliable, and fast.
Enable Artificial Intelligence (AI) and machine learning workloads across your environment that deliver on key business objectives.
Enhance business intelligence through analytics on all source data.
Transition to cloud services and architectures that prioritize security and governance.

Making the Most of Databricks

Databricks brings together data, analytics, and AI onto one platform. Are you maximizing its potential? This infographic provides 10 ways to be successful with Databricks, whether you’re a new or experienced user.

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Partnering with the best

Deep domain knowledge and certified skill sets across all major vendors set us apart from the rest.

Results you can measure

Clients working with Insight are solving their biggest data ingestion challenges with Modern Data Warehouse (MDW) expertise from Insight. Insight Lens, our proprietary architecture and set of processes, can help jump-start an MDW initiative.

In one instance, we helped a global electronic manufacturer retailer speed time to value and increase revenue with MDW implementation:

The challenge > The solution > The outcomes

Slow time to value for data scientists and analysts
Increasing engineering costs for data pipelines
Limited visibility and poor data flexibility
Complex data systems that strain users

Data mesh implementation and modern data analytics platforms

Difficulties finding and retaining skilled data management and analytics professionals
Intractable and complex data management environment
Inefficient data digestion or ingestion

Data lifecycle solutions that encompass analytics, AI, and business intelligence

Intense competitive pressures to grow and differentiate
Underutilized analytics
Rapid growth that compounds data ecosystem complexity
Outdated systems that can’t support AI and machine learning

Data estate modernization and integration of AI into existing applications

Featured content

National Restaurant Chain Commits to Data Modernization

Modern data architecture with an enterprise data warehouse enabled this national restaurant chain to reduce costs by $13,000 a month and better handle wait times, prep times, online ordering and delivery.

Read the client story

Major Insurance Provider Saves Big With Big Data Migration

Find out how a Fortune 500 annuities and life insurance company reduced cloud expenses by nearly 80% by working with Insight to shift from SAP Big Data Service to Azure HDInsight.

Read the client story