Data analytics services
Unlock the value in your data
Convert data to information, information to insights and insights to better business outcomes
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Unlock the value in your data
Convert data to information, information to insights and insights to better business outcomes
Luxoft offers data analytics services that ensure data integrity. Data teams receive support for everything they need to perform data quality functions — cleansing, normalization, validation and integration — and increased task automation.
Business data analytics solutions create a single source of truth, allowing companies to adopt more data-centric, service-driven approaches to data provision across the enterprise. Companies now engage in advanced analytics for decisioning.
Business users and engineers collaborate on business use cases, add value to datasets and bring the company into a data-driven decision-making era. Technology initiatives will align with business goals and further value opportunities.
Luxoft designs governance processes that open data for stakeholders to use. They address regulatory compliance and ensure that companies keep sensitive data safe without locking it away in insight-killing silos.
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Our aim is to help organizations move toward high-value enterprise analytics, no matter where they are in their journey.
Luxoft is a trusted partner, guiding clients toward becoming a data-driven organization. We help design and execute a road map for adopting technologies and solutions that deliver clean data and advanced analytics throughout the enterprise.
The diversity of our partner capabilities allows us to offer proven industry solutions from independent software providers. Luxoft supports clients as they adopt the cultural and organizational changes required to embed this more service-oriented approach.
We’re constantly expanding our capabilities to meet the rapid evolution of data technologies. We provide architecture, consulting and delivery capabilities across a wide array of solutions, focusing in particular on:
Personalizes customer experiences, improves efficiencies, and better mitigates risk.
For the design, deployment and management of AI applications.
With deep domain expertise and a solid track record of successful data and analytics projects, we help clients design and implement the best approach for deriving insights from data to drive new business and increase profitability.
We draw on a deep well of industry expertise from our global network of technology leaders. These innovators offer clients locally informed guidance for market-specific data challenges and regulatory requirements.
Custom enterprise-wide integrations ensure all clients derive value from data. We help automate the entire data lifecycle from ingestion to insight and ensure companies have the right foundation to shift to data-driven decision making.
From a next-generation home-automation service to data visualizations that improve delivery speed for a steel manufacturer, we’re using data and insights to fuel better business outcomes.
Data analytics consulting services can help businesses:
Our data and analytics services can help your organization:
MLOps (Machine Learning Operations) is meant to ensure that machine learning model deployment and maintenance are reliable and efficient. It’s a paradigm that brings together best practices and guidelines in the machine learning algorithm field.
MLOps is practiced by data scientists, DevOps engineers, and IT teams. Its benefits include enhanced efficiency, scalability, and risk mitigation at every stage of the machine learning model life cycle.
MLOps seeks to help enterprises meet the following goals:
Data privacy concerns the governance of sensitive data. It establishes how authorized parties can gain access to, modify, and use it. It also determines their roles and level of access, as well as how the data is collected and distributed. The notion of data privacy is the subject of multiple regulations, such as the General Data Protection Regulation in the European Union.
Data security, in turn, is the use of rules, practices, and technology meant to prevent unauthorized access to sensitive data and its corruption. It can involve introducing rule-based access to data, data encryption, and automated backups, among others.
Data security doesn’t guarantee data privacy: the data processor can still mishandle the collected personal data while keeping it secure. Data privacy, however, requires the data processor to have the capability to protect the data against theft, corruption, or unauthorized access.
The transformation into an insights-powered organization consists of:
