We Create Data Platforms

Our mission is to provide high quality “Data Engineering” services that fulfill our customers’data platform needs. Polar’s commitment is to make significant contributions to data engineering practices and become a leader in this rapidly growing industry.

Too often companies look to data scientists and ignore the fact that in order to be successful in data science, it is necessary to have an effective data platform. Polar sees the biggest skill gap is in high quality data engineers who can build these platforms. We believe the major reason for this gap is a scarcity of advanced software engineers and computer scientists.

Our extensive consulting experience in software development and programming fields enables our continuously developing expertise in software engineering best practices, computer science fundamentals, core database principles and recent advances in distributed systems. This expertise led to the creation of the Polar IT Services Data Engineering team.

The Polar Data Engineering team builds big data solutions. We design, develop, maintain, test and evaluate bespoke enterprise-level big data solutions. Our team focuses on collecting, parsing, managing, analyzing and visualizing large sets of data to turn customer information into actionable insights using multiple platforms. Our strong proficiency in data mining, machine learning, natural language processing, and information retrieval help create a robustportfolio of analytic solutions.

By creating these solutions in the cloud we reduce customer capital expenditure and infrastructure footprint.

Polar’s Technology Expertise

Our programming and architecture skillsets include the following:

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Big Data Engineering Life-Cycle

Below is a typical model for data engineering life-cycle

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Polar Data Engineering Activities

Our Data Engineering activities comprise, but are not limited to

Web Mining: Data compiled by mining websites. Our automated processes discover and extract information from Web documents and servers, and from unstructured data.

Search: Data compiled by mining browser activity, tracking search keywords and your customer’s behavior on your website.

Social Media: Data compiled by mining social media data on personal preferences, likes, “check-ins,” shares, and comments made by users.

Crowd Sourcing: Data compiled by mining multiple sources or large communities of people, including forums, surveys, polls, and other types of user-generated media.

Transactional: Data compiled by mining the real-time transactions involving activities such as purchases, requests, insurance claims etc.

Mobile: Data compiled by mining data that is created by mobile apps, customer usage patterns or other services working in the background.

Features and Benefits

Our approach ensures you can leverage the power of Big Data technologies by extending your current trusted infrastructure so you can do more at lower cost. We provide RESTful API that enables the data scientist to pull either exactly what they want or, alternatively, gives the means to access raw data and then build the final product.

Polar’s Data Engineering team builds data analytics ready platforms with

  • The power to run complex machine learning algorithms at scale
  • Integration with enterprise data flow and tools
  • Industry-specific security and compliance functions
  • Fault tolerance for mission critical data apps
  • The ability to handle up to an Exabyte of data on a daily basis
  • Data lakes to break down data silos

Polar’s services can be extended to

  • Create data-driven applications utilizing machine learning models which allow the app to grow and change when exposed to new data.
  • Build robust data marts and warehouses.
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