Idera, Inc. Acquires Qubole, Adds Data Lakes to Database Tools Unit

Qubole will join Idera’s database tools business unit that includes AquaFold, IDERA, Webyog, and WhereScape. The merger comes as Qubole hosts …

Idera, Inc. recently announced that it has acquired data lake tools solution provider Quboe, according to a press release. Qubole will join Idera’s database tools business unit that includes AquaFold, IDERA, Webyog, and WhereScape. The merger comes as Qubole hosts The Data Lake Summit in collaboration with AWS and Google Cloud. It also comes on the heels of Qubole’s launch of Qubole Pipelines Service. Unveiled in August, Qubole Pipelines Service enables users to build scalable streaming data pipelines.

Our Buyer’s Guide for Data Management Platforms helps you evaluate the best solution for your use case and features profiles of the leading providers, as well as a category overview of the marketplace.

Qubole’s flagship data management product is its Autonomous Data Platform, a solution that self-manages and self-optimizes by sending alerts and Insights and Recommendations (AIR) based on cloud agents connected to the customer’s data policies and preferences. Qubole uses a combination of heuristics and machine learning for workload continuity as well. Some of Qubole’s most notable customers include Expedia, Disney, ORacle, Fanatics, Activision Blizzard, and Adobe.

Idera offers an array of B2B software tools ranging from database administration to application development and test management. Under its broader data-centric tools umbrella, the vendor touts data warehouse automation, cross-platform database productivity, IT infrastructure monitoring, and database performance tools. Idera also acquired FusionCharts in March 2020 and WhereScape last September.

In a media statement about the news, Idera CEO Randy Jacops said: “Companies generate and store both structured and unstructured data at unprecedented levels. Qubole’s reputation as the leading cross-platform solution focused on unstructured data is a fantastic addition to Idera’s Database Tools division. In particular, it will pair well with Idera’s WhereScape business, the leading provider of data automation solutions for data warehouses.”

Read the official press release or learn more about Idera, Inc.

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Timothy King

Senior Editor at Solutions Review
Timothy is Solutions Review’s Senior Editor. He is a recognized thought leader and influencer in enterprise BI and data analytics. Timothy has been named a top global business journalist by Richtopia. Scoop? First initial, last name at solutionsreview dot com.
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AutoML in Practice

… knowledge of hyperparameter tuning (using grid search, random search, Bayesian optimization, and genetic algorithms) and will be exposed to new …

The compelling Oct. 15, 2019 presentation below is on behalf of one of my favorite Meetup groups: LA Machine Learning. The talk, “AutoML in Practice,” is by Danny D. Leybzon, a Solutions Architect at Qubole, a cloud-native big data platform. Before joining the Solutions team, he was the Data Science Product Manager at Qubole. Danny has an academic background in computational statistics. He believes that good data science requires good data engineering in order to create clean, accurate, and accessible data for data scientists. In the past, he’s given presentations on distributed deep learning, productionizing machine-learning models, and the importance of big data for machine learning in the modern world.

Automated Machine Learning (AutoML) is one of the hottest topics in data science today, but what does it mean? This presentation gives a broad overview of AutoML, ranging from simple hyperparameter optimization all the way to full pipeline automation.

After going over the theoretical framework and explanation of AutoML, he will dive into concrete examples of different types of AutoML. Danny will leverage Apache Spark (a framework popular with data scientists who need to scale machine learning workloads to Big Data) and Apache Zeppelin notebooks, as well as popular Python libraries such as Pandas, Plotly and bayes-opt.

Data science experts and novices alike will find this presentation accessible and enlightening. Participants will receive in-depth knowledge of hyperparameter tuning (using grid search, random search, Bayesian optimization, and genetic algorithms) and will be exposed to new tools for automating machine learning workflows.

The slides for this presentation are available HERE.

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Qubole Announces Webinar on Mastering Enterprise-Scale Big Data Analytics on Google Cloud …

SANTA CLARA, Calif., June 17, 2019 (GLOBE NEWSWIRE) — Qubole, the data activation company, today announced a webinar for data engineers …

SANTA CLARA, Calif., June 17, 2019 (GLOBE NEWSWIRE) — Qubole, the data activation company, today announced a webinar for data engineers and data scientists scheduled for 10 a.m. PDT on Wednesday, June 19 titled “Enterprise-Scale Big Data Analytics on Google Cloud Platform (GCP).” As companies scale their data infrastructure on Google Cloud, they need a self-service data platform with integrated tools that enables easier, more collaborative processing of big data workloads. Hosted by Anita Thomas, Principal Product Manager for Cloud Services at Qubole and Naveen Punjabi, Data Analytics Partnerships Lead, Google Cloud, the webinar is designed to provide best practices for data engineers and data scientists to scale their data infrastructure on Google Cloud.

Who: Naveen Punjabi, Data Analytics Partnerships Lead, Google Cloud

Anita Thomas, Principal Product Manager, Cloud Services at Qubole

What: Enterprise-Scale Big Data Analytics on Google Cloud Platform (GCP)

When: 10 a.m. PDT Wednesday, June 19, 2019

For more information and to register for the webinar, please visit the webinar home page.

The webinar will cover:

  • Why a unified experience with native notebooks, a command workbench and integrated Apache Airflow is a must for enabling data engineers and data scientists to collaborate using the tools, languages and engines they are familiar with.
  • The importance of enhanced versions of Apache Spark, Hadoop, Hive and Airflow, along with dedicated support and specialized engineering teams by engine, for your big data analytics projects.
  • How workload-aware autoscaling, aggressive downscaling, intelligent Preemptible VM support and other administration capabilities are critical for proper scalability and reduced TCO.
  • How you can deliver day-one self-service access to process the data in your GCP data lake or BigQuery data warehouse, with enterprise-grade security.

About Qubole

Qubole is revolutionizing the way companies activate their data–the process of putting data into active use across their organizations. With Qubole’s cloud-native Data Platform for analytics and machine learning, companies exponentially activate petabytes of data faster, for everyone and any use case, while continuously lowering costs. Qubole overcomes the challenges of expanding users, use cases, and variety and volume of data while constrained by limited budgets and a global shortage of big data skills. Qubole’s intelligent automation and self-service supercharge productivity, while workload-aware auto-scaling and real-time spot buying drive down compute costs dramatically. Qubole offers a platform that delivers freedom of choice, eliminating legacy lock in–use any engine, any tool, and any cloud to match your company’s needs. Qubole investors include CRV, Harmony Partners, IVP, Lightspeed Venture Partners, Norwest Venture Partners, and Singtel Innov8. For more information visit us online.

Media Contacts:

Orlando De Bruce Elena Keamy

Qubole Bateman Group for Qubole

odebruce@qubole.com qubole@bateman-group.com

Qubole Expands Partnership with Google Cloud for Processing Big Data on GCP

Qubole, provider of a cloud-native data platform for analytics and machine learning, has expanded its partnership and product integration with Google …

Qubole, provider of a cloud-native data platform for analytics and machine learning, has expanded its partnership and product integration with Google Cloud Platform (GCP).

Combining the capabilities of Google Cloud Platform with Qubole’s self-service data platform and tools for data science and data engineering, the companies say, the new offering enables easier processing of big data workloads with Apache Spark and Hadoop on Google Cloud, and connectors for data repositories such as Google Cloud Storage, Google BigQuery, Oracle, MySQL, Google Cloud Storage, Google BigQuery, Postgres, and MongoDB.

“Data is the new oil of this economy, and every day more companies are turning to the cloud to process data and leverage its value in their decisions,” said Mohit Bhatnagar, senior vice president of product, Qubole. “With this expanded partnership, Qubole is providing a powerful analytics service for Apache Spark and Hadoop on Google Cloud. Qubole’s solution delivers a unified workbench, notebooks and easy-to-use tools for data scientists and data engineers, enterprise-grade security, and 24×7 specialized support.”

Qubole is now available in public preview on Google Cloud Platform. For more information, visit Qubole.com.

Qubole partners with Google Cloud to improve data analytics experience

The “expanded partnership” will result in more collaborative processing of big data workloads with Apache Spark and Hadoop on Google Cloud.
Qubole partners with Google Cloud to improve data analytics experience
Qubole, a data activation and processing firm, has partnered with Google Cloud to enhance user experience in the field of data science and engineering.

Through the partnership and product integration with Google Cloud Platform (GCP), said the company, enterprises would get the option to deploy a new enterprise analytics service with a better user experience through a unified workbench that includes notebooks, dashboards, a native interface for all commands, and built-in tools for easy, secure collaboration.

For businesses, a Qubole on the cloud will help reduce the cost of operations for data analytics, said the company in the press release.

The “expanded partnership” will result in more collaborative processing of big data workloads with Apache Spark and Hadoop on Google Cloud.

This will also ensure access to many data sources such as Connectors for Google Cloud Storage, Google BigQuery, Oracle, MySQL, Postgres, MongoDB, and more.

“Data is the new oil of this economy and more companies every day are turning to the cloud to process data and leverage its value in their decisions,” said Mohit Bhatnagar, senior vice president of product, Qubole.

Google said it is bullish about acceptance of Qubole among its customers.

“We have a lot of customers who have been asking about some of these capabilities and Qubole actually fills that gap very well. Qubole is being highly adopted by large enterprise customers (especially) in the financial services domain (and) that is the market we can now cater to,” said Sudhir Hasbe, director of product management, Google Cloud, adding that “this partnership is all about providing our customers with the best options on GCP”.