A Control Plane for Data, and
a New Era for Acryl 

Shirshanka Das, Swaroop Jagadish

Jun 13, 2023

At Acryl Data, we are passionate about revolutionizing data management and empowering organizations to regain control of their fragmented data stacks. We do this first and foremost by driving the open source DataHub Project and collaborating with the largest metadata community in the world.

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Data ContractSnowflakeData GovernanceData DiscoveryData QualityComplianceHow ToBlogData CatalogMetadataOpinionArtificial IntelligenceMachine LearningMlopsData ManagementData EngineeringOpen SourceDataProject UpdatesDataHubDbtData PractitionerHumans of DataHubCommunityEngineeringOnboardingRbacAccess ControlData LineageStripeRemote WorkingTeam BuildingLineageDataHub CommunityDatabricksBest PracticesAnalyticsLookerData PlatformsBig DataData ScienceData InfrastructureFeaturesData VisualizationRelease NotesModern Data StackTech Deep DiveOpen Source SoftwareData Mesh

all posts

ALL POSTS

Metadata Management

Data Contract

Snowflake

Data Governance

Data Discovery

Data Quality

Compliance

How To

Blog

Data Catalog

Metadata

Opinion

Artificial Intelligence

Machine Learning

Mlops

Data Management

Data Engineering

Open Source

Data

Project Updates

DataHub

Dbt

Data Practitioner

Humans of DataHub

Community

Engineering

Onboarding

Rbac

Access Control

Data Lineage

Stripe

Remote Working

Team Building

Lineage

DataHub Community

Databricks

Best Practices

Analytics

Looker

Data Platforms

Big Data

Data Science

Data Infrastructure

Features

Data Visualization

Release Notes

Modern Data Stack

Tech Deep Dive

Open Source Software

Data Mesh

Governing the Kafka Firehose

Kafka’s schema registry and data portal are great, but without a way to actually enforce schema standards across all your upstream apps and services, data breakages are still going to happen. Just as important, without insight into who or what depends on this data, you can’t contain the damage. And, as data teams know, Kafka data breakages almost always cascade far and wide downstream—wrecking not just data pipelines, and not just business-critical products and services, but also any reports, dashboards, or operational analytics that depend on upstream Kafka data.

May 7, 2024

When Data Quality Fires Break Out, You're Always First to Know with Acryl Observe

Acryl Observe is a complete observability solution offered by Acryl Cloud. It helps you detect data quality issues as soon as they happen so you can address them proactively, rather than waiting for them to impact your business’ operations and services. And it integrates seamlessly with all data warehouses—including Snowflake, BigQuery, Redshift, and Databricks. But Acryl Observe is more than just detection. When data breakages do inevitably occur, it gives you everything you need to assess impact, debug, and resolve them fast; notifying all the right people with real-time status updates along the way.

John Joyce

Apr 23, 2024

Five Signs You Need a Unified Data Observability Solution

A data observability tool is like loss-prevention for your data ecosystem, equipping you with the tools you need to proactively identify and extinguish data quality fires before they can erupt into towering infernos. Damage control is key, because upstream failures almost always have cascading downstream effects—breaking KPIs, reports, and dashboards, along with the business products and services these support and enable. When data quality fires become routine, trust is eroded. Stakeholders no longer trust their reports, dashboards, and analytics, jeopardizing the data-driven culture you’ve worked so hard to nurture

John Joyce

Apr 17, 2024

Data Quality Should be Part of the Data Catalog - Introducing Acryl Observe

We didn’t go looking for an excuse to develop a data observability solution. There’s more than enough to keep us occupied building the world's best data catalog! ;) But the more experience we gained in working closely with Acryl customers, the clearer it became that data quality, data discovery, and data governance aren’t just complementary, but mutually reinforce one another. Acryl Observe provides data teams with everything they need to detect data breakages immediately, contain their downstream impact, keep stakeholders in the loop, and resolve issues fast—so that data teams can spend less time reacting and more time preventing.

John Joyce

Apr 16, 2024

Metadathon - Why MetaData Matters

Vaidehi Sridhar, product manager at PayPal, came up with a clever solution: a hackathon—but for documentation and metadata. The goal of Sridhar’s and PayPal’s “Metadatathon” was to crowdsource the labor involved in documenting and adding rich context to the company’s distributed data assets. “Lack of documentation was one of the major problems most of our users called out,” Sridhar explains.

Stephen Swoyer

Apr 16, 2024

Hack Your Way to Data Quality with a "Metadatathon"

PayPal Product Manager Vaidehi Sridhar probably wouldn’t call herself a mastermind, but she did execute on a genius idea to improve data quality across PayPal’s sprawling ecosystem. Even better, Sridhar and her team laid the groundwork for PayPal to federate data governance for its decentralized teams—as well as automate many types of tedious governance tasks. The genius idea? A metadata hackathon, or “Metadatathon.”

Stephen Swoyer

Mar 19, 2024

Metadata’s Role in Sustainable, Cost-Effective AI Development

Hear that sound? It’s the sound a turntable makes when its stylus jumps the groove and skids across a record. It’s a sign the party has suddenly and irreversibly come to an end. Something like this may be happening with AI, as the best-laid plans of teams building AI solutions crash up against the operational complexity involved in scaling and maintaining them.

Stephen Swoyer

Mar 18, 2024

Acryl Cloud for ML and AI Practitioners

When organizations struggle to operationalize ML or AI solutions, the root causes are usually data-related. ML and AI teams can’t find the data they need to define use cases, engineer features, or train their models. When they can find it, they can’t always use it—because they don’t know what it is, where it came from, who created it, when, or for what purpose. Lacking context, any dataset is a black box. Discover why a modern data catalog and metadata platform is a foundational element of any ML or AI platform.

Harshal Sheth

Jan 31, 2024

Making Data Relevant Again

Increasingly, decision-makers and stakeholders just don’t trust their data and analytics—usually because what they’re seeing is out-of-date, incomplete, inconsistent, and sometimes flat-out wrong.

Swaroop Jagadish

Jan 29, 2024

Acryl Cloud For Data Leaders and Practitioners

Data work is a true team sport. Each and every data asset is the product of a clear distribution of labor, with people in a diversity of roles—including data practitioners, software developers, architects, governance authorities, and business domain experts—working collaboratively.

Swaroop Jagadish

Dec 11, 2023

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