In accordance with a current survey, knowledge engineers are reporting almost twice as many knowledge incidents this 12 months as final. On common, it takes 15 hours per incident to achieve a decision. And almost 75% of the time, enterprise stakeholders are the primary to establish knowledge points. As knowledge leaders know, when enterprise customers encounter knowledge that’s lacking, faulty, or in any other case inaccurate, decision-making is compromised and belief in knowledge erodes.
That’s why we’re excited to announce that uniting various knowledge workforce personas to collectively guarantee knowledge high quality simply bought simpler, due to a brand new integration between Monte Carlo’s knowledge observability platform and Atlan’s lively metadata platform.
Collectively, these market main instruments make it attainable for firms that depend on knowledge for a aggressive benefit to grasp and enhance knowledge high quality, whereas making certain knowledge customers have all of the context they want, inside their current workflows, to make knowledgeable selections with knowledge.
Monte Carlo provides groups end-to-end knowledge observability via automated detection, alerting, and incident decision for knowledge high quality points. Atlan is a house for various knowledge groups, serving as a single supply of reality that prompts metadata throughout the fashionable knowledge stack to allow new modalities of collaboration. And each platforms already present deep integrations throughout the fashionable knowledge stack, together with Slack, Snowflake, dbt, Databricks, Sigma, and Fivetran.
Now, these two platforms work in tandem to supply knowledge groups with enhanced visibility into key knowledge operations and granular insights for knowledge asset discovery and exploration. Knowledge customers can simply entry up-to-date details about the standard of knowledge property earlier than they use them, streamlining collaboration throughout the group whereas constructing belief in knowledge.
How companies can leverage Monte Carlo + Atlan
With Monte Carlo and Atlan, groups can acquire an up-to-date understanding of their knowledge well being, construct belief in knowledge, and assist revolutionary new methods to method distributed knowledge infrastructure.
Extending visibility into knowledge well being
Groups utilizing Monte Carlo and Atlan can now shortly perceive the well being of particular knowledge property throughout their Knowledge Property. Knowledge standing updates in Atlan about knowledge well being are knowledgeable by Monte Carlo, and knowledge groups can now view displays and checks created for every manufacturing desk.
“Earlier than we modernized our knowledge stack, our knowledge monitoring was very reactive,” stated Michael Weiss, Senior Director of Product Administration (NAM, Knowledge Entry and Analytics) at NASDAQ. “The pipeline would possibly succeed, however we wouldn’t know if the info was proper, flawed, or detached. With Monte Carlo and Atlan, we will catch knowledge incidents early on, and supply everybody with clear visibility into the present standing of knowledge accuracy. That is proving priceless and has been essential for the chief workforce to trust we will ship on our promise of dependable, reliable knowledge.”
By extending visibility into knowledge well being, knowledge groups can work proactively to resolve points quicker and guarantee any impacted enterprise customers are conscious of potential downstream impacts.
Rising knowledge belief and collaboration throughout the enterprise
With this new integration, knowledge customers can view particulars of the newest knowledge incidents and anomalies detected by Monte Carlo. This helps all knowledge workforce personas, no matter technical skillset, to maintain shut tabs on the reliability of any given asset, primarily based on a standard metadata management airplane.
“With 1,600 staff serving over 1,000 purchasers with actionable, data-driven insights, we churn via huge volumes of knowledge each day,” stated Kenza Zanzouri, Knowledge Governance Strategist at Contentsquare. “Our inside groups are at all times centered on creating worth with new dashboards, fashions, or knowledge explorations, so making certain that knowledge is dependable is crucial. With Monte Carlo and Atlan, we’ve been in a position to shift from guide checks and testing to automated knowledge high quality protection—and make it readily obvious to enterprise customers when knowledge property could also be impacted by high quality points. This helps us scale in the long run and enhance communication between departments.”
By dramatically enhancing visibility throughout knowledge operations and streamlining communication, thereby enabling wider belief in knowledge, knowledge customers and engineers can work with knowledge in additional environment friendly, collaborative, and revolutionary methods.
Enabling domain-oriented knowledge administration
Ahead-thinking knowledge organizations are more and more shifting to undertake distributed knowledge architectures just like the knowledge mesh. Monte Carlo and Atlan assist present these knowledge groups with peace of thoughts about knowledge reliability, which generally is a problem when property are owned by area groups and obtainable via self-serve entry.
“At BairesDev, we offer main companies around the globe with know-how groups on demand, and applied an information mesh method to attain knowledge high quality, availability, and efficiency throughout our group,” stated Matheus Espanhol, Knowledge Engineering Supervisor at BairesDev. “Automation is an absolute necessity to attain sturdy knowledge governance throughout decentralized domains. With Monte Carlo and Atlan working in tandem, we will automate knowledge high quality requirements whereas sustaining visibility into how every workforce follows international insurance policies and units native insurance policies inside the area.”
With end-to-end visibility into knowledge well being and a centralized supply of reality, it’s now attainable for knowledge groups to facilitate self-serve analytics with out compromising on governance and high quality requirements.
How the mixing works
With this new integration, Atlan and Monte Carlo work collectively seamlessly to centralize info and communication about knowledge high quality.
Knowledge incidents detected by Monte Carlo can be surfaced in Atlan, with all of the context wanted to grasp precisely what and the place knowledge has been impacted. When incidents are resolved, they’ll be cleared—that means an absence of incidents signifies all is nicely with a given asset. What’s extra, any Monte Carlo customized displays can be recorded as native property in Atlan, offering the road of sight for knowledge customers to the underlying knowledge high quality framework applied with Monte Carlo.
By uniting a wider spectrum of knowledge personas, Monte Carlo and Atlan allow the activation of knowledge shopper enterprise context, such that this priceless IP may be productionized to additional advance knowledge belief and a deeper tradition of knowledge high quality.
The combination takes 5 minutes or fewer to configure, with no API use wanted, and all knowledge is accessible by way of the Atlan Chrome extension. This implies groups can entry wealthy metadata context instantly within the workflows the place they use the underlying property, similar to Knowledge Clouds, Lakehouses, Warehouses, and widespread Enterprise Intelligence tooling
Get began right now
To study extra about constructing belief in knowledge with Monte Carlo and Atlan, discover our documentation.
Create an account-service API key
Configure the mixing in 5 minutes (with interactive walkthrough)
Metadata sourced from Monte Carlo
Prepared to begin enhancing your knowledge high quality with end-to-end knowledge observability and cataloging? Attain out to request a Monte Carlo demo to see knowledge observability in motion or begin a free trial with Atlan to see knowledge collaboration work.