Collecting, storing, distributing, and using data quickly and efficiently is one thing. But data truly comes to use when you can send the relevant data to the people who need it, when and how they need it. We use the unique cloud-built data architecture and data platform called Snowflake to build data-intensive applications without creating any operational burden on our users. Thus, we tap into data modernization to help you respond quickly to changing market trends.
Enterprise Data Management
Financial details, photos, videos, mobile, IoT data - with data coming in daily, you need a way to organize, manage, and retrieve it. Enterprise Data Management helps create and maintain confidence and trust in your data assets through a streamlined and standardized system.
Building Data Lake
Creating a data lake such that different data sets are added consistently is challenging. We help you select the right data lake technology and relevant tools to set up the data lake solution consistently, ensuring that you don’t have to incur huge costs.
Hybrid Cloud Computing
Is your computing and processing demand going far beyond your on-premises datacenter’s capabilities? Cloud migration to scale your capacity can work. Hybrid cloud computing is build to manage excess capacity. Save time and cost of purchasing, installing, and maintaining new servers.
Data Warehouse Architecture
Gain from a directory that includes past information from several sources: used by employees of your organization to analyze, draw insights, and forecast the future. It takes information from raw data sets and stores it in a structured way for your people to use.
A crucial deployment decision in your digital transformation journey, cloud deployment includes all the required installation and configuration steps to be implemented. You can choose from public, private, community or hybrid clouds, depending on your infrastructure.
ETL to ELT
Finally, moving to the cloud? Embrace a better data transformation architecture using ELT. ETL extracts data from the source, transform it and loads it on a data warehouse. While ELT extracts data from the source load on the data warehouse, then transforms it.