We help our customers in all steps
of their Big Data Journey
We help our customers in all steps
Strategy & Roadmaps
Our practitioner uses a proven approach to establish an information-driven strategy leveraging all data and information for smarter business outcomes. The next level of detail is the development of a roadmap that will accelerate information-intensive projects aligned with the strategy to speed both short-term & long-term return on investments
Platform Implementation
Our big data consultant and engineer are experts in deploying open and agile technology that can leverage existing information assets with speed and flexibility
Data Ingestion, Batch and Streaming
Our team is capable to handle data inflow from disparate data sources into the cluster environment using either open source tools (Flume, Sqoop, Kafka) or proprietary products (Informatica, Knime, Alteryx) to provide flexibility in building applications in congruence with Lambda architecture. We also have expertise in building such a scalable ETL frameworks using functional programming libraries running on Apache Spark.
Data Management
We have the suitable skills to empower data stewards to ensure the transparency, security, reproducibility, auditability and consistency of the Data Lake and the assets it contains by using tools such as Apache Atlas and Apache Ranger. Our people will assist data managers, operations, and compliance personnel to visualize a data lineage and then drill down into operational, security and provenance-related details.
Data Engineering/Data Query
We have internalized the common application patterns with Spark and Hive using NoSQL data stores. This knowledge is being utilized in building generic application modules such as real time serving engines, API services using scalable microservices in the backend. These modules are dockerised to accelerate their customisation.
Virtualisation
Our team is equipped to use multi-purposed web-based notebooks such as Apache Zeppelin, Jupyter; which brings data ingestion, data exploration, visualisation, sharing and collaboration features to Hadoop and Spark. This is an agile approach which shortens conception to consumption cycle making the complexity of the environment transparent to the model builders and visualisation experts.
Data Science
Our data science team live and breath data. Their passion is to gain meaningful insights from all of the data and information that organisations have access to with the sole purpose of optimising the business performance. Team is well versed with Machine Learning, Deep Learning frameworks such as H20, Tensorflow, R
Data Visualisation
Analytics are better consumed visually. Our team is equipped with skills to create visualisations with commercial tools like Tableau, Qlik. We also have capability to build programmatic custom web based visualisations with D3.js