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Digital transformation efforts are placing a sharp focus on disparate data sources. As companies aim to speed business value, they’re realizing the need for data agility. But they’ve got a problem: most data sits in segmented silos, warehouses, data lakes, databases — and even spreadsheets, video files and the like.

“Databases and data lakes are more like data vaults,” Isaac Sacolick, President of StarCIO and author of Driving Digital, told CIO. “Business people know there’s value in the vault and often make deposits, but they don’t have adequate tools to know when, where, and how to get insights from it.”

At the same time, it is becoming increasingly complex to manage disconnected data sources, especially when budgets are constrained and data teams must do more with less.

Meanwhile, the volume of data is rising every day, with an expected 59 zettabytes expected to be created and consumed by the end of 2020, according to IDC. The analyst firm reports that COVID-19 has contributed to an abrupt increase, as well as “changing the mix of data being created to a richer set of data that includes video communication and a tangible increase in the consumption of downloaded and streamed video.”

The first step toward addressing these challenges: CIOs must solve the data integration issue.

Data integration, not application integration

Organizations need the ability to integrate all data sources — clouds, applications, servers, data warehouses, etc. Doing so maximizes the value of existing infrastructure investments, streamlines the data warehouse, reduces workloads and IT backlogs, and crucially, puts valuable data at business users’ fingertips.

Enterprises may try to resolve the data integration issue through application integration and system orchestration. Yet in terms of achieving speed to insight, or integrating data for the purpose of answering business questions, this is not an optimal solution. Given the world’s increasing demand for flexibility, modularity and composability, deep application integrations are not ideal for this. It is also time-consuming, can cause business disruption, and may add complexity to data warehouses with constant updating of analytical cubes and new operational processes.

A cloud-based analytics platform, with the right controls and governance in place, puts the right data into the right users’ hands in a single environment. This approach integrates data into automated pipelines, delivering data value while also achieving governance, control and actionable insights.

Cloud-scale integration

Domo seamlessly integrates data from any application, system or source across the entire business and beyond, transforming it to be used more effectively across every endpoint. All at cloud scale, with Domo Integration Cloud.

The cloud-based analytics platform turns data integration into a one-stop shop that provides:

  • Integration and automation. Domo prevents dark data by automating the ingestion, cleaning and blending of data from any source — cloud, data warehouse, legacy systems, user desktops — without the need to build new data warehouse. Data can also be fed into any business intelligence or artificial intelligence/machine learning platform, or other system, for further analysis.
  • Governance and control. IT can give users the data they need for analysis — in the tools they want to use — with granular access rights. Plus, IT retains control with access and data-flow monitoring capabilities built to the best in security standards and compliance certifications.
  • Performance. Ensure that data and processes flow at speed with Domo’s massive parallel processing functionality. Also, provide users with self-service capabilities to quickly request dataset access with a few clicks.

Domo gives organizations the cloud data integration capabilities to dynamically integrate data from thousands of sources and systems. With a single source of truth, users can finally glean value from a vault’s worth of data.

Learn more about how Domo Integration Cloud helps address the data integration issue.