Expertise

Big Data solution is art transforming of large and complex data into the enemy graphs and clusters of data. It does not matter how much data you have, but it’s usage can drive business forward and find the ways out of bottlenecks. The transformation process includes collecting, storing, processing, analyzing, sharing, transferring of data, moreover, it’s visualization, querying and updating. This is the alternative for traditional data management systems, which gives to the business an opportunity of making data-driven decisions with main concepts as volume, velocity, variety and veracity

Data management gives opportunity to the company to react flexible to the changeable market environment, manage growing data volumes. We are providing such services as data architecture, modeling and design, quality, storage and operations, security, integration and interoperability, data warehousing and business intelligence, meta-data, documents and content, reference and master data. Data by its own is not a knowledge, but data management includes various approaches from preparation, creation and storage to archiving or even destruction of data, which also regulates how company should deal with different types of data. The goals of data management are to ensure data availability in a perfect quality and terms of user’s needs, to bring together and exchange of data between different data sources, to governance data in big data environments and so on. Data quality, making sure that data is accurate, relevant and can fits further usage, is our prior task in the data management process.

Big data

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Enterprise Data Architecture

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Data lake/data reservoir architecture

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Cloud

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Data Integration

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BI layer

Enterprise Data Architecture

    • Big data warehouse architecture
    • Data warehousing in the cloud
    • Master Data Management (MDM). Integrating MDM with your data warehouse
    • Architecting a data warehouse error hospital for monitoring data quality
    • Data warehouse modelling
    • Architecting and integrating a data science platform into your data architecture

Data lake/data reservoir architecture

    • Align data lake strategy with the wider data and business strategy
    • Help in getting best storage format for your scenario
    • Data ingestion process design
    • PII data masking
    • Data governance
    • Metadata and data catalog management

Cloud

    • Assess and evaluate your current workloads
    • Physical and virtual server configurations
    • Network topology
    • Design an appropriate migration strategy
    • Migration to the cloud as per timelines agreed

Data Integration

    • Data Integration
    • Data mapping detailed technical design
    • Extracting data from legacy systems and production databases
    • Loading initial primer and incremental synchronization into target solution
    • System and service level monitoring
    • Assist in determining data growth trends and peak business periods

BI layer

    • Data Analysis, Profiling and Mapping
    • Report and navigation design
    • Semantic layer creation
    • Dashboard and layout design
    • Security Implementation