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Every modern business has access to vast amounts of data. The challenge is to harness this chaotic flow of structured and unstructured data and press it into service for advanced analytical applications. Handling this volume, variety, and velocity of data requires management architectures, agile processes, and specialized tools to extract insights faster and with greater precision.

LTIMindtree has been working with global customers to enhance their Big Data ecosystems (Hadoop, AWS Redshift, Azure Synapse, Google Big Query) so they can get insights into their customer needs, forecast disruptions and align operations, predict demand, drive innovation, improve the effectiveness of marketing strategies, etc.

Our Big Data services make it easy for enterprises to handle diverse batch and streaming processing loads, manage data variety and velocity and build scalable solutions for distributed computing. The outcome: Reduced time to insight, superior governance, reliable data, and higher ROI from data assets.

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    Resources

    Case Study
    POV
    Survey

    Engineering supply chain efficiency for one of the largest o...

    Optimizing data engineering pipelines to reduce write-offs and processing time from 24 to 6 hours for improving perishables availability for customers.

    Leveraged distributed architecture to increase a European Ai...

    Use historical sales data stored in Hadoop to engineer price elasticity estimator to forecast future demands and offer optimal seat price to customers.

    Scalable and shared analytical platform for an investment fi...

    Delivered a cloud-based scalable cost-effective platform on performance analytics for a UK-based global investment firm.

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    Customer data platform: Delivering extraordinary data-driven...

    Building an integrated data ecosystem that delivers personalized experiences in real time to increase purchases, build brand loyalty, and prevent churn.

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    Winning in the age of personalization

    The survey discovers where organizations are in their digital journey, how consumers are perceiving digital experiences, and consumer expectations.

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