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Anomalo Partners with Google Cloud

Anomalo announced a partnership with Google Cloud to help organizations trust the data they use to make decisions and build products.

The combination provides customers with a way to monitor the quality of the data in any table in BigQuery’s platform without writing code, configuring rules or setting thresholds.

Today’s modern data-powered organizations are using BigQuery to perform real-time, predictive analytics on their centralized data and build and operationalize machine learning (ML) models at scale. However, dashboards and production models are only as good as the quality of the data that powers them. Many data-powered companies quickly encounter one unfortunate fact: much of their data is missing, stale, corrupt or prone to unexpected and unwelcome changes. As a result, companies spend more time dealing with issues in their data rather than unlocking that data’s value.

Anomalo addresses the data quality problem by monitoring enterprise data and automatically detecting and root-causing data issues, allowing teams to resolve any hiccups with their data before making decisions, running operations or powering models. Anomalo uses ML to automatically assess for a wide range of data quality issues, including deep data observability that learns when there’s an unexpected trend or correlation inside the data itself. If desired, enterprises can fine-tune Anomalo’s monitoring using no-code key metrics and validation rules or by defining any custom SQL check.

With Anomalo, organizations can now begin monitoring the quality of their data in less than five minutes. They simply connect Anomalo’s data quality platform to their BigQuery account and select the tables they wish to monitor. No further configuration or code is required.

“Organizations using data to make decisions or as an input into ML models need to ensure accuracy and quality. With Anomalo’s continuous monitoring, customers can ensure their data is always accurate, even as it evolves over time,” said Naveen Punjabi, Director, Analytics & Data Science Partnerships, Google Cloud.

“I have always been a fan of Google Cloud’s customer centric approach to building products. BigQuery has allowed customers to democratize access to data and connect more source systems than ever before to unlock new BI and ML use cases. But next-generation ML and analytics solutions are only as good as the data they’re built on. Enterprises need deep data observability tools like Anomalo that can help them detect and resolve complicated data issues, before issues affect BI dashboards and reports or downstream ML models,” said Elliot Shmukler, Co-founder and CEO of Anomalo.

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Anomalo Partners with Google Cloud

Anomalo announced a partnership with Google Cloud to help organizations trust the data they use to make decisions and build products.

The combination provides customers with a way to monitor the quality of the data in any table in BigQuery’s platform without writing code, configuring rules or setting thresholds.

Today’s modern data-powered organizations are using BigQuery to perform real-time, predictive analytics on their centralized data and build and operationalize machine learning (ML) models at scale. However, dashboards and production models are only as good as the quality of the data that powers them. Many data-powered companies quickly encounter one unfortunate fact: much of their data is missing, stale, corrupt or prone to unexpected and unwelcome changes. As a result, companies spend more time dealing with issues in their data rather than unlocking that data’s value.

Anomalo addresses the data quality problem by monitoring enterprise data and automatically detecting and root-causing data issues, allowing teams to resolve any hiccups with their data before making decisions, running operations or powering models. Anomalo uses ML to automatically assess for a wide range of data quality issues, including deep data observability that learns when there’s an unexpected trend or correlation inside the data itself. If desired, enterprises can fine-tune Anomalo’s monitoring using no-code key metrics and validation rules or by defining any custom SQL check.

With Anomalo, organizations can now begin monitoring the quality of their data in less than five minutes. They simply connect Anomalo’s data quality platform to their BigQuery account and select the tables they wish to monitor. No further configuration or code is required.

“Organizations using data to make decisions or as an input into ML models need to ensure accuracy and quality. With Anomalo’s continuous monitoring, customers can ensure their data is always accurate, even as it evolves over time,” said Naveen Punjabi, Director, Analytics & Data Science Partnerships, Google Cloud.

“I have always been a fan of Google Cloud’s customer centric approach to building products. BigQuery has allowed customers to democratize access to data and connect more source systems than ever before to unlock new BI and ML use cases. But next-generation ML and analytics solutions are only as good as the data they’re built on. Enterprises need deep data observability tools like Anomalo that can help them detect and resolve complicated data issues, before issues affect BI dashboards and reports or downstream ML models,” said Elliot Shmukler, Co-founder and CEO of Anomalo.

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An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...

In March, New Relic published the State of Observability for Media and Entertainment Report to share insights, data, and analysis into the adoption and business value of observability across the media and entertainment industry. Here are six key takeaways from the report ...

Regardless of their scale, business decisions often take time, effort, and a lot of back-and-forth discussion to reach any sort of actionable conclusion ... Any means of streamlining this process and getting from complex problems to optimal solutions more efficiently and reliably is key. How can organizations optimize their decision-making to save time and reduce excess effort from those involved? ...

As enterprises accelerate their cloud adoption strategies, CIOs are routinely exceeding their cloud budgets — a concern that's about to face additional pressure from an unexpected direction: uncertainty over semiconductor tariffs. The CIO Cloud Trends Survey & Report from Azul reveals the extent continued cloud investment despite cost overruns, and how organizations are attempting to bring spending under control ...

Image
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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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