Project Types

Change the way you approach data infrastructure projects  

Whether you’ve already chosen a model for your data infrastructure project, or are still exploring which model is best for your business, one thing should be clear: automating the development lifecycle is a critical success factor.   

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Data Warehouse

Virtually every organization wants to be more data driven. A data warehouse provides a central repository for extracting insights and informing decisions. The challenge is how to deliver and update data warehouses at the speed the business needs.

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Data Mart

One of your business functions needs a specific set or subject area of data—now. You’re thinking providing a data mart could meet their needs but, based on previous traditional methods, it’ll take months. Unless, that is, you automate 80 percent of the development effort.

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Data Vault

Created with data warehousing best practices, Data Vault 2.0 is a methodology for delivering data warehouses that are more adaptable to change. Data vault automation takes the complexity out of design and development and makes Data Vault 2.0 an achievable reality.

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Big Data

Apply the big A of automation to the five Vs of big data – volume, variety, velocity, variability and veracity –and achieve rapid integration into your enterprise data infrastructure. Big data integration that will yield big insights for your organization.

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Cloud

While cloud data warehousing lets you take advantage of the scalability, resiliency, and cost-effectiveness of the cloud, it’s still up to you to design, develop, deploy and operate your data infrastructure. Automation can put you on the cloud fast track.

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Streaming

Integrate real-time data within your data infrastructure to create new possibilities for data science, machine learning, anomaly detection and more. Easily ingest and process streaming data into your company's data infrastructure alongside traditional data sources with automation.

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