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Harness data-driven insights

At Terralogic, we mine data, treat and repeat the process until it yields results.

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What you need is to build

Resilient data science roadmaps

At Terralogic, we build data science road maps to aid different organizations in solving their unique problems.

We are industry competent with the process of harnessing data-driven insights for initiating new businesses, advising strategic changes, or accessing new markets.

WHY DO YOU

Need to go data-driven?

We practice supervised learning towards substantial data monitoring, that watches over all the means to identify vulnerable operations and take needful preventative measures in real-time. We put into use a wide variety of machine learning algorithms like Linear Regression, Regression tree, R-programming, and dispersion analysis to provide actionable business insights.

  • Design Language & Style Guide

    Analyzing data sets

    Every organization collects a wide variety of data and only by asking the right questions and assessing data in combination with complementary information will yield actionable results.

  • Design Language & Style Guide

    Internet of things

    Make the data flow from the stream of data meant for connected devices, to process for value-added operational analytics. This is how we optimize the supply chain of asset management.

  • Design Language & Style Guide

    Machine Vision

    Make the data flow from the stream of data meant for connected devices, to process for value-added operational analytics. This is how we optimize the supply chain of asset management.

Expertise

At Terralogic,

We develop Complete
end-to-end data analysis

Our analysis depends on a lot of perspectives that benefit your business. We build smart analytics that helps all kinds of businesses from start-ups to industry giants to maximize the value of their data, unearth insights, build plans and respond in real-time to customer demand.

Go beyond the what. Get to the why, and plan for what’s next.

Sentiment Analysis

At Terralogic, we use Text Data Analytics to understand the most varied responses to a product experience so that the organization can take measures to redress the situation.

Expertise
Expertise

Predictive Analysis

Using historical data also yields results that can be used to predict future growth and development. Predictive analysis can be done on the basis of the company and industry-centric data alike.

FREQUENTLY ASKED

Questions

  • All system, application, user, and patient data is backed up nightly and encrypted at the file level. All servers are updated regularly with the latest security patches, and they run on a dedicated network protected by firewalls, intrusion-detection systems, and controlled access points. That's how our Data Engineering service works.

    • The business knows that there’s gold in all that data, and your team’s job is to find it. But being a detective with a bunch of clunky tools and difficult to setup infrastructure is hard. You want to be the hero who figures out what’s going on with the business, but you’re spending all your time wrestling with the tools.

    • We built Databricks to make big data simple. Apache Spark™ made a big step towards achieving this mission by providing a unified framework for building data pipelines. Databricks takes this further by providing a zero-management cloud platform built around Spark that delivers.

      - fully managed Spark clusters,

      - an interactive workspace for exploration and visualization,

      - a production pipeline scheduler,

      - a platform for powering your favorite Spark-based applications. So instead of tackling data headaches, you can finally focus on finding answers that make an immediate impact on your business.

  • Yes. We use the very best and the latest in software, technology and infrastructure for our Data Engeneering service. By outsourcing you can save on investing on expensive software and technology as we use the very best in both. All our office have best-of-breed infrastructure.

  • There are two types of models we're using in Data Engeneering technology: predictive and descriptive. Descriptive models are good to explain what has happened and what is happening. Predictive models explain what would be happening and why. These models are increasingly being utilized to solve problems across finance, marketing, human resource, operations and other business functions.

Our 15 years of achievements includes:

  • 10M+

    lines of codes

  • 2400+

    projects completed

  • 900+

    satisfied clients

  • 16+

    countries served

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