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We develop Big Data solutions for cloud and local settings.

BlueSoft is helping to create a Data Lake for one of Poland’s leading banks.

 

You may have data without information, but you can’t have information without data

Daniel Keys Moran

What does Big Data mean for us?

Big Data is a term that refers to large data sets – both structured and unstructured – processing of which exceeds the capabilities of conventional databases and commonly available methods and algorithms. According to the most popular definition, published in 2001 by META Group (now Gartner), Big Data is the “3V model”, that is:

  • Volume – large amounts of data
  • Velocity – high variability of data
  • Variety – variety of data

Yet, the sheer amount of data is not the most important. What is essential is the way in which companies and organizations may use this data. Pooling Big Data resources and advanced data analysis may produce quantifiable results in such realms as:

  • Risk analysis
  • Product improvement
  • Faster response to customer requirements
  • Process optimization
  • Anomaly and error detection
  • Predictive analysis
Big data, how does it work

BlueSoft in the world of Big Data

Data Ingestion

We build comprehensive solutions that enable data acquisition, while taking into account the multitude of sources and formats. Data may be loaded both in real time and in batches.

Our solutions are based both on the tools available on the market (e.g. NiFi, Amazon Kinesis, Sqoop, Kafka), as well as on dedicated components designed and implemented to particular specifications.

Storage

We have many years’ experience in developing distributed structured and unstructured data storage systems, whose characteristics tie in perfectly with the 3V Big Data model (Volume, Velocity, Variety).

We have successfully implemented multiple projects using NoSQL databases (e.g. Apache Cassandra, HBase, MongoDB, Redis), Data Lakes based on distributed file systems, for instance HDFS and Amazon S3.

Batch and Real-time processing

Depending on an instance, we use two data processing methods: – online – real-time data processing (quick reaction to occurring events) – offline – batch processing of large data sets (for the purposes of creating analytical models and reports).

Moreover, we develop efficient solutions using the lambda architecture, which makes the most of both data processing methods.

Analytics

We create comprehensive analytical platforms based on well-known and most common tools and libraries used in the world of Data Science.

We pick programming languages to meet client’s expectations, so regardless of whether your team is proficient at Python, Java or Scala, our solutions will make your data analysts’ work exceptionally easy and pleasurable.

Visualisation

We streamline the analysis process by developing comprehensive platforms for visualizing the gathered and processed data. Owing to such tools as Tableau and Plotly, as well as the D3.js library, analysis results become even more valuable. Big Data has been evolving from mere numbers that are not very easy on the eyes and the visual layer has enabled greater interaction with the data, which makes its presentation more engaging and understandable for the end user.

Process automation

We implement distributed data processing systems using installation and administration process automation tools. Additionally, we help streamline Big Data process management based on Continuous Integration and Continuous Delivery practices. We also put much emphasis on automation and standardization of the data processing itself.

Our services in Big Data

  • Big Data in the cloud (AWS)
  • Dedicated solutions for Big Data
  • Consultancy
  • Data Ingestion Tools
  • Data visualization
  • Searching Big Data
  • DevOps in Big Data
  • Lambda Architecture
  • Real Time Processing / Streaming
  • Business Intelligence in Big Data
  • Business Case Validation
  • Expanding MDM with Big Data
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