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Based on a latest survey, knowledge engineers are reporting practically twice as many knowledge incidents this 12 months as final. On common, it takes 15 hours per incident to achieve a decision. And practically 75% of the time, enterprise stakeholders are the primary to determine knowledge points. As knowledge leaders know, when enterprise customers encounter knowledge that’s lacking, misguided, 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 numerous knowledge workforce personas to collectively guarantee knowledge high quality simply obtained simpler, because of 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 corporations that depend on knowledge for a aggressive benefit to know and enhance knowledge high quality, whereas guaranteeing knowledge customers have all of the context they want, inside their present workflows, to make knowledgeable selections with knowledge.
Monte Carlo offers groups end-to-end knowledge observability via automated detection, alerting, and incident decision for knowledge high quality points. Atlan is a house for numerous 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. Information customers can simply entry up-to-date details about the standard of information belongings 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 achieve an up-to-date understanding of their knowledge well being, construct belief in knowledge, and assist modern 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 belongings throughout their Information Property. Information standing updates in Atlan about knowledge well being are knowledgeable by Monte Carlo, and knowledge groups can now view screens and checks created for every manufacturing desk.
“Earlier than we modernized our knowledge stack, our knowledge monitoring was very reactive,” mentioned Michael Weiss, Senior Director of Product Administration (NAM, Information Entry and Analytics) at NASDAQ. “The pipeline may succeed, however we wouldn’t know if the information was proper, improper, or detached. With Monte Carlo and Atlan, we are able to catch knowledge incidents early on, and supply everybody with clear visibility into the present standing of information accuracy. That is proving invaluable and has been vital for the manager workforce to have faith we are able to ship on our promise of dependable, reliable knowledge.”
By extending visibility into knowledge well being, knowledge groups can work proactively to resolve points sooner 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 most recent 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 aircraft.
“With 1,600 workers serving over 1,000 shoppers with actionable, data-driven insights, we churn via large volumes of information day by day,” mentioned Kenza Zanzouri, Information Governance Strategist at Contentsquare. “Our inside groups are at all times centered on creating worth with new dashboards, fashions, or knowledge explorations, so guaranteeing that knowledge is dependable is crucial. With Monte Carlo and Atlan, we’ve been capable of shift from handbook checks and testing to automated knowledge high quality protection—and make it readily obvious to enterprise customers when knowledge belongings could also be impacted by high quality points. This helps us scale in the long run and enhance communication between departments.”
By dramatically bettering 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 modern methods.
Enabling domain-oriented knowledge administration
Ahead-thinking knowledge organizations are more and more transferring 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 could be a problem when belongings are owned by area groups and out there via self-serve entry.
“At BairesDev, we offer main companies world wide with expertise groups on demand, and applied an information mesh method to realize knowledge high quality, availability, and efficiency throughout our group,” mentioned Matheus Espanhol, Information Engineering Supervisor at BairesDev. “Automation is an absolute necessity to realize sturdy knowledge governance throughout decentralized domains. With Monte Carlo and Atlan working in tandem, we are able to automate knowledge high quality requirements whereas sustaining visibility into how every workforce follows international insurance policies and units native insurance policies throughout 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 data and communication about knowledge high quality.
Information incidents detected by Monte Carlo might be surfaced in Atlan, with all of the context wanted to know 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 effectively with a given asset. What’s extra, any Monte Carlo customized screens might be recorded as native belongings 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 information personas, Monte Carlo and Atlan allow the activation of information client enterprise context, such that this invaluable IP might be productionized to additional advance knowledge belief and a deeper tradition of information high quality.
The combination takes 5 minutes or fewer to configure, with no API use wanted, and all knowledge is out there 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 belongings, comparable to Information Clouds, Lakehouses, Warehouses, and in style Enterprise Intelligence tooling
Get began in the present day
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 bettering 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.
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