San Francisco, CA, USA
Mar 9, 2023   |  By Kensu
Kensu announces a Product Advisory Council comprised of experienced data leaders to support the company's mission to provide Data Observability at the source through strategic guidance, enriching the Kensu product with insights from market needs.
Mar 9, 2023   |  By Robin Tandon
Recently I read a very informative article by Stephen Catanzano in Tech Target (Avoid data sprawl with a single source of truth). To be honest, this is an age-old challenge, and it's getting worse. IDC states that by 2025 the global datasphere will grow to 175 Zeta bytes and that 90% of the data in the world is a replica. Why does this matter? As Stephen points out in his article, a single source of truth is a fundamental concept in data management.
Feb 20, 2023   |  By Sammy El Khammal
Apache Spark has become one of the most popular open-source data processing platforms in the enterprise ecosystem, especially thanks to its ability to handle both batch and real-time data processing on large amounts of data.
Jan 27, 2023   |  By Robin Tandon
We often find it hard to remember the world we left behind, but cast your mind back, say, 20 years, and we lived in a very different world. Personal Computers and the internet were on the rise, and businesses were all becoming connected. This provided companies with immense opportunities in terms of collaboration and digital adoption, and on the flip side, it eased the distribution of computer viruses. Today we barely even think about our antivirus software and policies.
Jan 10, 2023   |  By Kensu
Kensu, the Data Observability company, announced today that it has partnered with Snowflake, the Data Cloud company, to better aid data practitioners in gaining full visibility into their real-time data with Snowflake's expansive data storage, processing, and analytics capabilities.
Jan 9, 2023   |  By Robin Tandon
As we move into 2023, I am very excited to see all of the predictions for data and analytics and what they mean to Kensu. I looked at different publications and spoke with various industry experts and analysts to see if there were any conclusions we could draw.
Jan 4, 2023   |  By Andy Petrella
As organizations look to scale up and improve the business value of their growing data volumes, certain data trends have garnered the attention of data and business professionals alike. With this growth promising to continue in the upcoming year, data leaders are looking to implement tools to enrich their organization’s data like never before. Here are seven trends you can watch for in the new year.
Dec 12, 2022   |  By Kensu
Observe your data pipelines and data sources in real-time to cut resolution time in half and restore trust in data.
Nov 1, 2022   |  By Kensu
Kensu announces its partnership with Collibra, the Data Intelligence company, and the availability of an integration between the two solutions. Kensu's observability capacities will enrich Collibra's Catalog with clean, trustworthy, and curated information to enable business users and data scientists to make business decisions based on reliable data.
Sep 12, 2022   |  By Kensu
Supporting the data community with the first free solution to monitor data pipelines and unleash the potential of this new category.
Oct 11, 2022   |  By Kensu
Quickly detect, troubleshoot, and prevent the propagation of a wide range of data incidents through Data Observability, a set of best practices that allow data teams to gain greater visibility of data and its usage. If you're a data engineer, ML engineer, or data architect, or if the quality of your work depends on the quality of your data, this book shows how to focus on the practical aspects of introducing Data Observability in your day-to-day work.

Our low latency data observability solution alerts about data issues, prevents their propagation, and highlights which applications are impacted.

To foster a data-driven culture, automation of data observability at scale is essential. The best way to achieve this is through what is called Data Observability Driven Development [DODD] which implies observable information is produced by the applications.

The method is a paradigm shift that allows data teams and data usage to scale efficiently. DODD is done from within the applications to enable data projects with synchronized observability, continuous validation, and contextual observability.

Data Observability is for everyone:

  • For Data Scientists: Remain confident about the models in production by being notified as soon as performance is deviating.
  • For Data Engineers: Save time and trouble by easily increasing your visibility and control over data in production.
  • For Heads of Data: Increase the productivity of your team by reducing the resources required to maintain existing data applications.
  • For Analysts: Increase trust in existing reports by being immediately alerted as soon as data quality is out of range.

Trust what you deliver.