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Telecom AI
Blog Post 3 min read

Extending the Competitive Advantage in Telecom

As the telecom industry navigates upcoming tech changes, machine learning and artificial intelligence are poised to drive the next frontier.
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Blog Post 15 min read

Real-Time Analytics for Time Series

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KPI analysis
Blog Post 6 min read

Business Leaders Can't Afford To Wait For Insights: How Self-Service BI is Changing Data Analysis

Continuous, accurate measurement of your primary KPIs is only half of the battle. The other half is turning all that data into actionable insights. Self-service BI is making it easier than ever.
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Blog Post 5 min read

Managing Structured Data, Unstructured Data and the In-Between

There’s a lot of confusion surrounding the differences between structured and unstructured data. To better understand why, let’s review which data formats the industry currently is using, and some of the challenges they pose.
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Blog Post 6 min read

Can Your Big Data Company Forego Anomaly Detection?

While enterprise leaders are constantly looking to innovate, there’s one area where “business as usual” should be a focus — spotting anomalies in your data.
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shutterstock_531055792
Blog Post 5 min read

How AI/ML Helps Retailers Keep 3 Promises This Holiday Season?

In the first part of our "Metrics At Scale" series, we start by examining multivariate anomalies and why correlation is key to root cause investigation.
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Blog Post 7 min read

A Small Leak Can Sink a Great Ship: Proactive Monitoring Keeps You Afloat

Small and slow leaks sink ships - by analogy, slow and small leaks can also cause significant losses for any business if not detected and fixed early.
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Blog Post 6 min read

Metrics At Scale: Using Correlation Analysis to Find Data Insights (Part 3)

In the final part of the "Metrics At Scale" series, we look at normal and abnormal behavior similarities, getting a sparse or lower dimensional vector representation, and creating a pattern matching engine.
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Blog Post 5 min read

You Can Improve Your Customer Satisfaction Charlie Brown!

The increasingly agile, data-driven approach to development, parsing user data and releasing new versions regularly, has left many in data operations at a loss. So how do you identify unknown unknowns happening right under your nose?
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