Semantix’s big data solutions are distinct since they are designed based on the requirements of the clients. The company’s engineers understand the issues faced by the clients and suggest a viable solution after signing a Non-Disclosure Agreement (NDA) with them. They take into account the nature of data involved in the organization and the kind of workflow that is needed to manage the data effectively and engineer an architecture, which will be deployed after the client’s consent. “We not only deploy customized solutions but also provide training to our clients to promote and accelerate adoption of new technologies that are added in the solutions,” states Santos.
Semantix’s big data solutions focus on four varied scenarios—big data search, ETL (Extract, Transform, and Load) and big data warehouse, heavy math analytics along with data science and machine learning, and real-time analytics. The company has partnered with Lucidworks, Cloudera, DataStax and Mesosphere to carryout big data analytics at a more detailed level and to provide training to clients to understand and leverage the solutions effectively.
Semantix doesn’t stay on the big data analytics field only. Recently the company has been moving to build big data apps that will provide valuable information for companies and public services. Semantix believes that this will drive innovation in many different ways.
Our solutions provide a smart search system enabling the clients to collaborate with their data in smarter manner
It efficiently designs and deploys data warehouse solutions based on big data technologies for its clients and also shifts solutions from SAS and mainframes to Spark and Mahout big data solutions. The company understands the challenges and simplifies the solutions since it is aware of the best practices for all the scenarios where data is the complex thing.
Semantix provides unparalleled big data solutions with two powerful strategies—providing a vast source of information to its clients and other is envisioning and designing big data products as well as selling them directly to the customers. The company allows its competitors to sell the products on its behalf to accelerate the sale of its products in the long run. The company uses open source software which provides the required agility during market fluctuations.
Semantix’s solutions provide a smart search system enabling its clients to collaborate with their data in smarter manner. For instance, a private bank was challenged with indexing an absolute database of more than one TB which was being transferred from mainframes. Semantix built a Spark-based indexer in Python to index the data with Apache Solr. It used around 20 servers for building a disaster recovery cluster to prevent fail over during breakdowns. It also increased speed with seven virtual servers, which indexed masses of data in three days which used to take two weeks when indexed with older servers. The bank also benefitted with other Solr features such as highlighting and hardcore faceting drill-down menus.
Moving ahead, Semantix is planning to expand its services across the globe. “We will expand our presence in Latin America and North America,” concludes Santos.