DataOps, MLOps

In today's data-driven world, managing vast volumes of big data has become increasingly complex. DataOps and MLOps emerged as cutting-edge approaches to tackle this challenge. DataOps aims to build an agile and efficient data infrastructure, maximizing the value organizations can derive from their data. On the other hand, MLOps is dedicated to automating machine learning processes through DevOps methodology, empowering businesses with seamless and effective machine learning implementations.

Data Modernization & Engineering Success Stories

Discover how we translate strategic innovation into differentiated capabilities and accelerate bottom-line impacts for fast-growing enterprises and digitally-native companies.

Challenge:

Avoid the inefficiencies resulting from manual incident management and slow development cycles.

Approach:

Developed performance monitoring dashboards, including real-time notifications.

Impact:

+39%

Monthly Releases

-8%

Issue Resolution
Time

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Challenge:

Streamline data assets to simplify and enhance analytical insights.

Approach:

Extracted insights with Data Science & Analytics and enhanced decision-making using real-time performance data.

Impact:

+50%

Site
Traffic

+200%

Conversion
Rate

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Challenge:

Mitigate data fragmentation, analytical challenges, slower site performance, and the decay of the customer experience.

Approach:

Deployed an integrated data warehouse, providing decision-makers with real-time performance visibility.

Impact:

+81%

Conversion
Rate

+364%

Daily
Transactions

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Thought Leadership for DataOps, MLOps

Allow us to show you our expert input and find out more about our work on emerging insights, challenges, and trends across industries worldwide.

Multivariate, Unsupervised, Scalable, Explainable and Robust Anomaly Detection - Part 3: Further Improvements & Results

Despite the many advantages brought by Robust Random Cut Forests (RRCF), as described in the ...

Deliver Better Analytics Faster with DataOps

How does DataOps lower the cost of asking analytic questions? Christopher Bergh is the CEO and Head ...

Introduction to MLOps

Introduction The growing demand for machine learning solutions (ML henceforth) in the mainstream ...

Data Mining on Azure ML Studio

What is Data Mining? Data Mining is a Knowledge Discovery in Databases (KDD) process, which ...

More Insights

Learn More About Encora

We are the software development company fiercely committed and uniquely equipped to enable companies to do what they can’t do now: More.

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Digital Engineering Services

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DataOps, MLOps

Data Modernization & Engineering Success Stories

Challenge:

Approach:

Impact:

+39%

-8%

Challenge:

Approach:

Impact:

+50%

+200%

Challenge:

Approach:

Impact:

+81%

+364%

Thought Leadership for DataOps, MLOps

Multivariate, Unsupervised, Scalable, Explainable and Robust Anomaly Detection - Part 3: Further Improvements & Results

Deliver Better Analytics Faster with DataOps

Introduction to MLOps

Data Mining on Azure ML Studio

Learn More About Encora

Nearshore
Services

Careers

Our Work

DataOps, MLOps

Data Modernization & Engineering Success Stories

Challenge:

Approach:

Impact:

+39%

-8%

Challenge:

Approach:

Impact:

+50%

+200%

Challenge:

Approach:

Impact:

+81%

+364%

Thought Leadership for DataOps, MLOps

Multivariate, Unsupervised, Scalable, Explainable and Robust Anomaly Detection - Part 3: Further Improvements & Results

Deliver Better Analytics Faster with DataOps

Introduction to MLOps

Data Mining on Azure ML Studio

Learn More About Encora

NearshoreServices

Careers

Our Work

Nearshore
Services