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Build Robust And Scalable Data Management Solutions

Data Management applies collection, validation, storing, and accessibility of data to fuel AI solutions, data analytics systems, and business intelligence software. The efficiency and accuracy of each of those platforms vastly depend on the quality of data, ensured by reliable data engineering solutions and scalable data management processes.

Well-tuned, effective, and secure big data management systems are the backbone and reason of success for outstanding data-driven companies: from disruptive startups to the leading Fortune 500 companies.

Advantages Of Modern Data Management Solutions

Data Quality

Nowadays, when businesses constantly gather vast amounts of data, it needs to be analyzed and transformed to gain actionable insights—otherwise, it’s a waste of valuable information. Big data management services can help efficiently process and validate data, eliminate duplicates and incompatible versions, structuring information by creating a rock-solid foundation for future analysis and fueling BI and AI solutions to make intelligent, data-driven decisions.

Data Value

Cutting-edge data management solutions enable processing of enormous amounts of data, including audio, video, and other types of unstructured information in a matter of seconds. Huge volumes and unsupported data types aren’t the barriers any more. Board members and key decision-makers can access the information immediately rather than waiting another month for a dedicated manager or legacy systems to craft a report.

Efficiency and Automation

Conventional data management approaches result in numerous data storages of inconsistent information that require significant time and effort to make use of it. Applying data engineering services and technologies leads to coherent big data management throughout the organisation, empowering consumers to meet their information needs better, quicker or even autonomously.

Data Security and Compliance

Data security is crucial for every business—unencrypted, fragmented, and uncontrolled access levels can lead to data breaches and reputational and financial risks. Comprehensive data management services can help incorporate robust data security that ensures vital company information is backed up, encrypted and stored in centralized and secure data storage. This allows conducting regular security audits and preventing unauthorized access and data leaks.

Big Data Management Solutions

  • Big data engineering and real-time processing

    Building data pipelines that consolidate information from multiple sources, and processing the data according to extract, transform, load (ETL) or extract, load, transform (ELT) methodologies. Big data management solutions empower businesses with a single source of trusted information, automated data reporting, and instant data-driven decisions.

  • Data lakes and data warehousing

    Building, configuring, or upgrading cloud-based data lakes and data warehouse solutions to store, manage and analyze information more efficiently. Data management storages can help address any data-related concern—from building a centralized data warehouse to reinforcing your existing system to have a high throughput and be more scalable, resilient, and secure.

  • Cloud-based big data management

    Configuring and implementing an off-the-shelf cloud solution from leading vendors such as Google, AWS, Azure, IBM to enable rapid deployment of holistic data engineering tools with minimal risk and implementation effort. Cloud-based data management platforms have the lowest entry barriers of cost, complexity, time-to-value, and they eliminate the risks inherent to the on-premises data warehouse.

  • Data migration

    Migrating data systems from an on-premise server to the cloud, from one enterprise system to another, and from various platforms, and analytic tools to optimize data storage and processing efficiency. Data migration solutions can transform every source into an enriched, relational data structure that allows your business to navigate big data better and make well-grounded decisions quicker.

  • Data governance and meta-data management

    Comprising a robust data catalog and ingesting descriptive information from various sources, presenting it as a consistent, reliable source. Master data management services can help eliminate duplicity, inconsistency, and make data much easier to find and process, increasing the information’s value and re-distributing the data to different systems.

  • Data fabric

    Building a full-fledged, distributed data fabric architecture that enables flexible, resilient data integration across platforms and business users, as well as a broad range of analytical, operational and governance use cases.

    Data fabric architecture automates data discovery, management and facilitates self-service consumption, empowering businesses with maximized value chain by leveraging data.

Contact Us to Discuss Your Big Data Needs

Our Big Data Management Services

  • End-to-end data management solutions

  • Reinforcement of data engineering team

  • Data infrastructure audit

  • Data engineering consulting

By bringing our in-depth data engineering competence we take care of all aspects of the data processing lifecycle—from the requirements stage all the way to launch and maintenance to a market-ready big data management solution.

We assemble a turn-key team that seamlessly increases your in-house capabilities, accelerates development, and decreases time-to-value of data management solutions.

Our data engineering experts can validate the state of your big data management practice, refine existing data strategies, and define a roadmap to optimize information processing, increase efficiency, and establish a sustainable foundation for intelligent data handling and analytics.

We bring profound knowledge, technical know-how of our data management consultants to help you identify the most suitable approach, tools, and technologies tailored for your specific business needs.

Big Data Solutions Partners

We are proud to partner with leading global organizations who provide cloud infrastructure for big data management. This motivates us to excel and offer our clients better data engineering services.

Data Management Process & Methodology

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  • 01/ Define business goals

    Identifying your key goals and dive deep into business processes, data workflow, deliverables to draft the best solution, and outline the scope of work.

  • 02/ Set up data collection

    Identifying your key goals and dive deep into business processes, data workflow, deliverables to draft the best solution, and outline the scope of work.

  • 03/ Raw data pre-processing

    Cleaning, transforming, and evaluating data quality to remove inaccurate records for further analysis. Composing the data management system architecture with best-fitted technology solutions.

  • 04/ Establishing data storage

    Building data storage based on the amount, types of data, and business goals and needs. Our data engineers make sure that your storage is secure and easily accessible only for authorized systems and users.

  • 05/ Integration in business

    Developing and smoothly implementing a data management solution into your business environment, assuring its performance and accuracy threshold on the real data.

  • 06/ Validation and improvements

    Establishing regular assessment of the data system’s performance, precision, throughput, and efficiency. Making adjustments if necessary.

Data Management Solutions For Industries

    • Reinforcing HRM, staffing, and recruiting software
    • Enhancement of benefits management solutions
    • Advance of business processes automation (BPA) systems
    • Secure and compliant enterprise data storages
    • Consistent data architecture ready for scale
    • Streamlined operational data processing
    • Quicker extraction of real-time stock market insights
    • Efficient big data processing for fraud detection
    • Background for intelligent, algorithmic trading
    • Big data for deep personalization and customization
    • Acceleration of liquidity analysis and risk management
    • Collection and real-time processing of health data
    • Personalized, value-based, patient care
    • Foundation for predictive analytics
    • Efficient use and handling of EHRs
    • Accessibility and security of PHI for authorized personnel
    • Data centralization across marketing channels into a single repository
    • Aggregation of big data, extraction of dependencies and insights
    • Real-time budget redistribution and optimization
    • Smart audience segmentation and personalization
    • Automated, real-time big data collection and instant processing
    • Processing data on students’ achievements, behavior, and ranking
    • Metadata enrichment and e-book management
    • Building enterprise data vault for future analytic solutions
    • Personalized student experiences
    • Video captioning and accessibility
    • Empowering your learning management system (LMS)
    • Consolidation of real-time GPS and weather data in a single system
    • Vehicle diagnostics, driving patterns, and location tracking data
    • Data-driven automation of warehouse operations
    • Improving lean manufacturing with real-time data from various sensors and devices
    • Intelligent, real-time routing of deliveries and distribution
    • Data for demand forecasting and precise targeting
    • Analysis of sales personnel performance and profitability
    • Intelligent inventory management and supply chain planning
    • Data consolidation from PoS systems, in-store sensors, and cameras
    • Accuracy improvement of risk assessment
    • Increasing performance of fraud detection
    • Customer data integration and client insight extraction
    • Efficient claims management
    • Flexible data and analytics infrastructure
  • Enterprise Software

    • Reinforcing HRM, staffing, and recruiting software
    • Enhancement of benefits management solutions
    • Advance of business processes automation (BPA) systems
    • Secure and compliant enterprise data storages
    • Consistent data architecture ready for scale
    • Streamlined operational data processing
  • Financial & Banking

    • Quicker extraction of real-time stock market insights
    • Efficient big data processing for fraud detection
    • Background for intelligent, algorithmic trading
    • Big data for deep personalization and customization
    • Acceleration of liquidity analysis and risk management
  • Healthcare

    • Collection and real-time processing of health data
    • Personalized, value-based, patient care
    • Foundation for predictive analytics
    • Efficient use and handling of EHRs
    • Accessibility and security of PHI for authorized personnel
  • Marketing & Advertising

    • Data centralization across marketing channels into a single repository
    • Aggregation of big data, extraction of dependencies and insights
    • Real-time budget redistribution and optimization
    • Smart audience segmentation and personalization
    • Automated, real-time big data collection and instant processing
  • Education

    • Processing data on students’ achievements, behavior, and ranking
    • Metadata enrichment and e-book management
    • Building enterprise data vault for future analytic solutions
    • Personalized student experiences
    • Video captioning and accessibility
    • Empowering your learning management system (LMS)
  • Logistics & Supply

    • Consolidation of real-time GPS and weather data in a single system
    • Vehicle diagnostics, driving patterns, and location tracking data
    • Data-driven automation of warehouse operations
    • Improving lean manufacturing with real-time data from various sensors and devices
    • Intelligent, real-time routing of deliveries and distribution
  • Retail & eCommerce

    • Data for demand forecasting and precise targeting
    • Analysis of sales personnel performance and profitability
    • Intelligent inventory management and supply chain planning
    • Data consolidation from PoS systems, in-store sensors, and cameras
  • Insurance

    • Accuracy improvement of risk assessment
    • Increasing performance of fraud detection
    • Customer data integration and client insight extraction
    • Efficient claims management
    • Flexible data and analytics infrastructure

Data-Powered Growth for Every Industry

Buzz Sharifi photo

Buzz Sharifi

Account Manager at TransGrade, CRM

Noam Shalit photo

Noam Shalit

COO at SafeRide Technologies Ltd

Ilya Kottel photo

Ilya Kottel

VP R&D at HumanEyes

Eric Spear photo

Eric Spear

SVP of Engineering at Cengage

Christian Rohner photo

Christian Rohner

Project Manager at Information Products AG

Success Stories

We really care about project success. At the end of the day, happy clients watching how their application is making the end user’s experience and life better are the things that matter.

View all success stories

ETL Process into SaaS Increased Performance

Retail & eCommerce

Success Story ETL Process into SaaS Increased Performance image

Data Engineering Solution For Hospitals

Healthcare

Success Story Data Engineering Solution For Hospitals image

SaaS Platform for Health Data Analysis

Healthcare

Success Story SaaS Platform for Health Data Analysis  image

SaaS Solution for Health Data Management

Healthcare

Success Story SaaS Solution for Health Data Management image

Web Platform with Predictive Algorithms

Healthcare

Success Story Web Platform with Predictive Algorithms image

Data Processing BI System for Healthcare

Healthcare

Success Story Data Processing BI System for Healthcare image
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Data Engineering Technologies Stack

FAQ on Big Data Management And Data Engineering Services

01/

How can big data analytics benefit financial services?

Big data analytics in finance and banking can help assess and manage risk faster and more effectively. Properly implemented big data management solutions can effectively process big data for fraud detection, accelerate liquidity analysis and open up access to predictive analytics capabilities. Big data services and consulting enable financial and banking organizations to leverage the power of unstructured and big data, predict financial trends, and identify competitive advantages through deep customization and customization. We are located in the US and can help you develop for efficient big data management and lay the foundation for future analytics.

02/

How can big data help to improve healthcare services?

Big data management and consulting in healthcare can save lives by predicting high-risk patients faster, predicting treatment outcomes, generating real-time alerts, and reducing medical errors.  Big data management consulting enable healthcare services to gain actionable insights into patient data, reduce overall healthcare costs, enable efficient electronic health record management, and serve as the basis for predictive analytics. Real-time processing of medical data allows for a better understanding of patients and more personalized patient care, thereby improving overall outcomes. Robust big data management and data lake engineering services keep PHI accessible and secure for authorized personnel, reducing the leakage of sensitive data.

03/

What percent of companies that use big data solutions are satisfied?

According to NewVantage Venture Partners Survey, 56.5% of companies report that big data initiatives help to drive business innovation and accelerate their decision-making. It’s a a bright spot against a backdrop of slow progress and considerable room for improvement. The application of big data to business initiatives is transforming the way we do business and laying the groundwork for future analytics. NIX is located in the USA and provides big data management and consulting services to help you get started with data initiatives and accelerate your data processes.

04/

Why would an enterprise-level company need big data consulting?

Adoption and implementation of big data solutions can be tricky, especially if you don’t have enough in-house expertise or you want to focus on higher-value business activities while delegating this task to professionals. At NIX, we provide big data consulting services to help you identify the most suitable approach, tools, and technologies tailored for your specific business needs. 

Max is our senior practice leader and evangelist for the “big triad” of machine learning, data analytics and data engineering, with a vast background in AI, BI services, and product management.

Big Data & Data Science Practice Leader

Max is our senior practice leader and evangelist for the “big triad” of machine learning, data analytics and data engineering, with a vast background in AI, BI services, and product management.

An AI Solutions Consultant with more than 10 years of experience in business consulting for the software development industry. He always follows tech trends and applies the most efficient ones in the software production process. Finding himself in the Data Science world, Evgeniy realized that this is exactly where the cutting-edge AI solutions are being adopted and optimized for business issues solving. In his work, he mostly focuses on the process of business automation and software products development, business analysis and consulting.

Applied AI & Data Science Solutions Consultant

An AI Solutions Consultant with more than 10 years of experience in business consulting for the software development industry. He always follows tech trends and applies the most efficient ones in the software production process. Finding himself in the Data Science world, Evgeniy realized that this is exactly where the cutting-edge AI solutions are being adopted and optimized for business issues solving. In his work, he mostly focuses on the process of business automation and software products development, business analysis and consulting.

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