Data Engineering

Our expertise in advanced analytics is backed by strong capabilities in data engineering for both traditional and big data needs. Whether it is fetching and managing data, or building and integrating analytics solutions, our engineers are intimately familiar with state-of-the art technologies, and customize the solution per client needs and constraints.

We have worked on a variety of web mining problems, whether it is fetching data using APIs or scrubbing. With our expertise in large scale data processing and natural language processing algorithms, we have analyzed large volumes of unstructured data (e.g. tweets, posts, and blogs) providing real-time insights to businesses.

While traditional RDBMS solutions like MySQL or MS SQL Server are efficient in several cases, some situations warrant a NoSQL data management solution. Our big data architects have designed and implemented Hadoop systems, and are very familiar with technologies such as MapReduce, Hive, and Pig. We have executed scalable machine learning projects in a big data environment using open source technologies.

We develop algorithms in a language best suited for integration into client systems (Java, Python, C++, Php). We have delivered analytics solutions as libraries, APIs, algorithms, and product enhancements. Some are stand-alone desktop tools while other are massively parallelized cloud-based solutions.