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About Us

We Are CoreLogiQ

We are a team of engineers with experience building big data solutions for organizations that have some of the world's largest information management systems.

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What We Do

We build Big Data Solutions

We build custom information management solutions for very large datasets (Big Data) that when stored in traditional database storage systems render them unsuitable for data analyatics due to their slow performance. Our solutions are fast, scalable, continuosly available, cost effective and are powerful enough to be able to perform different types of analytics such as predictive and behavior analytics.

Our solutions are cloudy ready and have been designed to take advantage of distributed computing resources, where available. This provides scalability as the amount of data and the number of users grow.

We also provide the ability to geo-replicate the data across cloud availability zones across the globe. This ensures continuous availability in the event of a failure and also allows the storage/retrieval of data from the closest availabiliy from the source increasing transmission efficiency and reducing latency.

As various cloud providers have availability zones in different geographic regions. We, optionally, provide the ability to replicate data between different cloud providers creating a hybrid cloud system that provides coverage in regions that provide the best latency and throughput for our clients.

In order to address data security and privacy concerns we also provide the ability to store data in encrypted form so that data privacy is maintained even in the event of a data breach.

How we are different

We love what we do

At Corelogiq, our focus is on developing solutions that are custom tailored for a specific problem based on an in-depth analysis of the nature of data involved.

Most big data solutions today are built by simply gluing together free or open source technologies and developing generic solutions. While such solutions work well in simple and low to medium sized applications they start to become expensive once size of data and users increase. The cost of hardware involved in horizontal scaling, data replication and bandwidth will grow rapidly making these solutions prohibitively expensive.

By getting a deeper understanding of the nature of the data involved and addressing the intricacies of storage, transmission and use of data, including analytics, we are able to develop solutions that are lightning fast, scale well and cost effective.

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