Big Data Services

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Custom big data services

Intellias experts offer a full range of big data services, from consulting and strategy definition to infrastructure maintenance and support, enabling our clients to get vital insights from previously untapped data assets. We apply a proprietary big data framework combined with popular open-source technologies like Apache Hadoop, Spark, and Kafka as well as machine learning and deep learning algorithms to deliver a comprehensive tool set for storing, processing, and analyzing large quantities of data.
  • Big data consulting

    Big data consulting

    Leverage our big data consulting services to assess and optimize your current big data solution, define a product strategy, and identify best-fit technologies that will help you convert your data into revenue opportunities.

  • Data infrastructure & engineering

    Data infrastructure & engineering

    Create data warehouse and data lake solutions, as well as streamline ETL development, execution and management tasks by building data pipelines that transform raw data into curated datasets which can be easily retrieved for further processing.

  • BI & data analytics

    BI & data analytics

    Make better and faster decisions by accelerating your time to insights using breakthrough business intelligence tools and leveraging a data science approach that comprises statistical and machine learning techniques.

  • Data visualization

    Data visualization

    Gain 360-degree visibility into your data with interactive reports and intuitive dashboards that make analytics understandable and manageable for everyone at every level of your organization.

  • Data security

    Data security

    Protect your data from intentional and accidental destruction, modification, or disclosure by adhering to security standards, developing a tiered access system, and ensuring efficient backup and recovery processes.

  • Data monetization

    Data monetization

    Embed analytics into your products and services to reveal insights that enable you to improve your overall business performance, strengthen customer loyalty, and help you detect new growth opportunities.

Uncover operational insights from previously untapped data sources

Success storiesView all case studies

BI reporting solution for online gambling

EveryMatrix, a top provider of industry-leading SaaS solutions for iGaming operators, required to revamp their business intelligence reporting system to smoothly process the increasing amounts of data coming from customers’ CMSs and payment operators, as well as efficiently manage their 100 TB data warehouse. Intellias team developed powerful mechanisms to aggregate and process data from all EveryMatrix products and provide data-driven insights for end customers and partners.

Learn more BI reporting solution for online gambling

Geospatial big data platform

A global provider of geospatial services and mapping solutions for automotive giants has set its sight on making a quantum leap in building the future of an autonomous world. In close partnership with Intellias, they were able to release a development platform for custom geolocation solutions comprising operations on large volumes of datasets and a marketplace that enabled secure data enrichment and transfer for enterprises across different industries.

Learn more Geospatial big data platform

Consumer engagement analytics platform

A Fortune 500 multinational retailer with a presence in over 180 countries required a holistic solution for centralized control over the complex network of retail data acquisition services. We helped our client build a data lake for collecting and storing telemetry data and logs from microservices, as well as set up a comprehensive monitoring tool with custom dashboards to keep track of the whole sales cycle, from order to delivery.

Learn more Consumer engagement analytics platform

ML-powered SaaS landing solution

An Arizona-based SaaS lending solutions provider decided to build a platform that would serve as a bridge between individuals who are looking for funds to grow their businesses and banks that can issue loans. Intellias team has covered the entire backend development for the platform, as well as contributed to the creation of a credit score calculator that leverages data collected on borrowers’ businesses and ML algorithms to potentially automate the loan giving process.

Learn more ML-powered SaaS landing solution

Data lake management platform

The first German digital bank with a rapidly growing customer base required to meet increased demand for custom solutions from the end-client' side by launching a comprehensive data management system. Intellias experts helped our client build the data lake platform for effective aggregation of extensive data from various services and microservices, including Oracle, SQL, web files, and local file copies, as well as use this data as a basis for further analysis and customization of digital banking services.

Learn more Data lake management platform

Additional benefits of working with Intellias

Big Data Center of Excellence with leading experts to conquer the most challenging tasks

Extensive AI skill set for accurate predictions based on data modelling

Profound cloud competency covering the AWS, Microsoft Azure, and Google Cloud platforms

Top-tier UI/UX expertise to present complex data to users in a visually appealing manner

Our approach

  1. 1

    Define the problem

    Assess your business environment and performance to identify key goals and challenges

  2. 2

    Collect data

    Gather data in different formats from multiple sources to address identified goals

  3. 3

    Prepare data

    Evaluate data quality and remove inaccurate records to structure data for further analysis

  4. 4

    Analyze data

    Develop analytical algorithms to discover useful insights for making business decisions

  5. 5

    Incorporate in business

    Integrate analytical algorithms into your production environment to unlock new opportunities

  6. 6

    Validate the results

    Continuously assess the performance of your algorithms and make adjustments if necessary

1

Define the problem

Assess your business environment and performance to identify key goals and challenges

2

Collect data

Gather data in different formats from multiple sources to address identified goals

3

Prepare data

Evaluate data quality and remove inaccurate records to structure data for further analysis

4

Analyze data

Develop analytical algorithms to discover useful insights for making business decisions

5

Incorporate in business

Integrate analytical algorithms into your production environment to unlock new opportunities

6

Validate the results

Continuously assess the performance of your algorithms and make adjustments if necessary

Big data analytics for enterprise data management

Smart decision-making

As the data landscape evolves, companies need to be more agile and responsive. Predictive analytics helps to join big data processing and practical decision-making. Big data analytics services and data science transform the way enterprises deal with information.


If companies don’t want to be deluged by volumes of high-velocity data, they need to quickly react to market challenges and think outside the box. Big data analytics solutions enable companies to inspect, clean, and model data to draw valuable, business-oriented conclusions. Visualizing big data analytics allows business leaders to quickly make sense of information and provides real-time insights to identify new opportunities.

Competitive edge

Thoroughly gathered and explored data is critical for reacting to future challenges. Enterprises that can recognize emerging tendencies and tailor their services accordingly can meet rising demand and become the go-to sources for particular products or services.


Big data predictive analytics puts actionable insights directly into the hands of decision-makers, helping companies stay ahead of the competition. The correct use of data intelligence lets companies review their internal operations and workflows to effectively expand their services and investments. Big data analytics solutions help executives reduce time and expenses on product development and marketing strategies to outperform their rivals.

Data-driven organization

Today’s data environment poses lots of challenges for a big data analytics company. With the rise of distributed and cognitive computing, companies need to manage unstructured forms of data. Putting it to good use is the key to becoming a strong data-driven organization.


By using advanced analytics techniques powered by artificial intelligence (AI) and machine learning (ML) algorithms, business owners can unlock the value of their data. Big data analytics company can shape actionable models from existing data to predict possible scenarios and help companies determine which actions will bring the best results. Analyzing consumer preferences and distributing the results of analysis across departments makes this data the key asset for any enterprise.

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Awards and recognition

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