Big Data & Analytics

Embrace Big Data Analytics for More Informed Decision-Making

Big data is a set of approaches, tools and methods for processing huge volumes of structured and unstructured data to obtain human-readable results.

Big data is a set of approaches, tools and methods for processing structured and unstructured data of huge volumes and significant diversity to obtain human-perceived results that are effective in conditions of continuous growth, distribution over numerous nodes of a computer network. Big data solutions are a smarter alternative to traditional database management systems and Business Intelligence solutions.

Softarex engineers have extensive experience in designing and developing big data systems for various industries such as Healthcare, Manufacturing and Energy, Banking and Finances. Read more>>

Stages of big data solutions development:

  • Requirements collection and analysis, data analysis and research
  • Crowdsourcing (data collection and preparation)
  • Converting data into a single standard form
  • Machine learning and neural networks
  • Predictive analytics
  • Imitational modeling
  • Statistical analysis
  • Data mining
  • Data visualization (including design of visual data representation)
Agile & SCRUM

Main principles of working with Big Data

Horizontal scalability

Any system processing big data must be scalable

Fault tolerance

If any of the machines in the cluster fails, the whole system will continue to work.

Locality of data

Since in large distributed systems, data are spread across multiple compute nodes and data storage, data should be processed on the machine where they are stored.



Hadoop, Python, Scala, Spark



AWS, Google Cloud, Microsoft Azure, Heroku, Kafka



MongoDB, Cassandra, Redis

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