Best Data Quality Software for Snowflake

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.

Satori is a Data Security Platform (DSP) that enables self-service data and analytics for data-driven companies. With Satori, users have a personal data portal where they can see all available datasets and gain immediate access to them. That means your data consumers get data access in seconds instead of weeks. Satori’s DSP dynamically applies the appropriate security and access policies, reducing manual data engineering work. Satori’s DSP manages access, permissions, security, and compliance policies - all from a single console. Satori continuously classifies sensitive data in all your data stores (databases, data lakes, and data warehouses), and dynamically tracks data usage while applying relevant security policies. Satori enables your data use to scale across the company while meeting all data security and compliance requirements.

It shouldn't take long to analyze data from your business solutions. Zuar Runner allows you to automate your ELT/ETL processes, and have data flow from hundreds of sources into one destination. Zuar Runner can manage everything: transport, warehouse, transformation, model, reporting, and monitoring. Our experts will make sure your deployment goes smoothly and quickly.

QuerySurge is the smart Data Testing solution that automates the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Applications with full DevOps functionality for continuous testing. Use Cases - Data Warehouse & ETL Testing - Big Data (Hadoop & NoSQL) Testing - DevOps for Data / Continuous Testing - Data Migration Testing - BI Report Testing - Enterprise Application/ERP Testing Features Supported Technologies - 200+ data stores are supported QuerySurge Projects - multi-project support Data Analytics Dashboard - provides insight into your data Query Wizard - no programming required Design Library - take total control of your custom test desig BI Tester - automated business report testing Scheduling - run now, periodically or at a set time Run Dashboard - analyze test runs in real-time Reports - 100s of reports API - full RESTful API DevOps for Data - integrates into your CI/CD pipeline Test Management Integration QuerySurge will help you: - Continuously detect data issues in the delivery pipeline - Dramatically increase data validation coverage - Leverage analytics to optimize your critical data - Improve your data quality at speed

Twilio Segment’s Customer Data Platform (CDP) provides companies with the data foundation that they need to put their customers at the heart of every decision. Using Twilio Segment, companies can collect, unify and route their customer data into any system. Over 25,000 companies use Twilio Segment to make real-time decisions, accelerate growth and deliver world-class customer experiences.

INGEST. PREPARE. DELIVER. ALL WITH A SINGLE TOOL. Build a data infrastructure capable of ingesting, transforming, modeling, and delivering clean, reliable data in the fastest, most efficient way possible - all within a single, low-code user interface. ALL THE DATA INTEGRATION CAPABILITIES YOU NEED IN A SINGLE SOLUTION. TimeXtender seamlessly overlays and accelerates your data infrastructure, which means you can build an end-to-end data solution in days, not months - no more costly delays or disruptions. Say goodbye to a pieced-together Frankenstack of disconnected tools and systems. Say hello to a holistic solution for data integration that's optimized for agility. Unlock the full potential of your data with TimeXtender. Our comprehensive solution enables organizations to build future-proof data infrastructure and streamline data workflows, empowering every member of your team.

OvalEdge, a cost-effective data catalogue, is designed to provide end-to-end data governance and privacy compliance. It also provides fast, reliable analytics. OvalEdge crawls the databases, BI platforms and data lakes of your organization to create an easy-to use, smart inventory. Analysts can quickly discover data and provide powerful insights using OvalEdge. OvalEdge's extensive functionality allows users to improve data access, data literacy and data quality.

Key Features of Syncari ADM: Continuous Unification & Data Quality Programmable MDM with Extensibility Patented Multi-directional Sync Integrated Data Fabric Architecture Dynamic Data Model & 360° Dataset Readiness Enhanced Automation with AI/ML Datasets, Metadata as Data, Virtual Entities Syncari’s cohesive platform syncs, unifies, governs, enhances, and provides access to data across your enterprise, delivering continuous unification, data quality, and distribution—all within a scalable, robust architecture.

A platform for data management powered by AI that allows data democratization. Insights drives innovation by integrating and centralizing all data sources, facilitating collaboration, and empowering organizations for innovation. SCIKIQ, a holistic business platform, simplifies the data complexities of business users through a drag-and-drop user interface. This allows businesses to concentrate on driving value out of data, allowing them to grow and make better decisions. You can connect any data source and use box integration to ingest both structured and unstructured data. Built for business users, easy to use, no-code platform, drag and drop data management. Self-learning platform. Cloud agnostic, environment agnostic. You can build on top of any data environment. The SCIKIQ architecture was specifically designed to address the complex hybrid data landscape.

Immuta's Data Access Platform is built to give data teams secure yet streamlined access to data. Every organization is grappling with complex data policies as rules and regulations around that data are ever-changing and increasing in number. Immuta empowers data teams by automating the discovery and classification of new and existing data to speed time to value; orchestrating the enforcement of data policies through Policy-as-code (PaC), data masking, and Privacy Enhancing Technologies (PETs) so that any technical or business owner can manage and keep it secure; and monitoring/auditing user and policy activity/history and how data is accessed through automation to ensure provable compliance. Immuta integrates with all of the leading cloud data platforms, including Snowflake, Databricks, Starburst, Trino, Amazon Redshift, Google BigQuery, and Azure Synapse. Our platform is able to transparently secure data access without impacting performance. With Immuta, data teams are able to speed up data access by 100x, decrease the number of policies required by 75x, and achieve provable compliance goals.

Coginiti is the AI-enabled enterprise Data Workspace that empowers everyone to get fast, consistent answers to any business questions. Coginiti helps you find and search for metrics that are approved for your use case, accelerating the lifecycle of analytic development from development to certification. Coginiti integrates the functionality needed to build, approve and curate analytics for reuse across all business domains, while adhering your data governance policies and standards. Coginiti’s collaborative data workspace is trusted by teams in the insurance, healthcare, financial services and retail/consumer packaged goods industries to deliver value to customers.

DQOps is a data quality monitoring platform for data teams that helps detect and address quality issues before they impact your business. Track data quality KPIs on data quality dashboards and reach a 100% data quality score. DQOps helps monitor data warehouses and data lakes on the most popular data platforms. DQOps offers a built-in list of predefined data quality checks verifying key data quality dimensions. The extensibility of the platform allows you to modify existing checks or add custom, business-specific checks as needed. The DQOps platform easily integrates with DevOps environments and allows data quality definitions to be stored in a source repository along with the data pipeline code.

Decube is a comprehensive data management platform designed to help organizations manage their data observability, data catalog, and data governance needs. Our platform is designed to provide accurate, reliable, and timely data, enabling organizations to make better-informed decisions. Our data observability tools provide end-to-end visibility into data, making it easier for organizations to track data origin and flow across different systems and departments. With our real-time monitoring capabilities, organizations can detect data incidents quickly and reduce their impact on business operations. The data catalog component of our platform provides a centralized repository for all data assets, making it easier for organizations to manage and govern data usage and access. With our data classification tools, organizations can identify and manage sensitive data more effectively, ensuring compliance with data privacy regulations and policies. The data governance component of our platform provides robust access controls, enabling organizations to manage data access and usage effectively. Our tools also allow organizations to generate audit reports, track user activity, and demonstrate compliance with regulatory requirements.

Data visibility and control for security, compliance, privacy, and governance. BigID's platform includes a foundational data discovery platform combining data classification and cataloging for finding personal, sensitive and high value data - plus a modular array of add on apps for solving discrete problems in privacy, security and governance. Automate scans, discovery, classification, workflows, and more on the data you need - and find all PI, PII, sensitive, and critical data across unstructured and structured data, on-prem and in the cloud. BigID uses advanced machine learning and data intelligence to help enterprises better manage and protect their customer & sensitive data, meet data privacy and protection regulations, and leverage unmatched coverage for all data across all data stores.

Ataccama is a revolutionary way to manage data and create enterprise value. Ataccama unifies Data Governance, Data Quality and Master Data Management into one AI-powered fabric that can be used in hybrid and cloud environments. This gives your business and data teams unprecedented speed and security while ensuring trust, security and governance of your data.

Anomalo helps you get ahead of data issues by automatically detecting them as soon as they appear and before anyone else is impacted. -Depth of Checks: Provides both foundational observability (automated checks for data freshness, volume, schema changes) and deep data quality monitoring (automated checks for data consistency and correctness). -Automation: Use unsupervised machine learning to automatically identify missing and anomalous data. -Easy for everyone, no-code UI: A user can generate a no-code check that calculates a metric, plots it over time, generates a time series model, sends intuitive alerts to tools like Slack, and returns a root cause analysis. -Intelligent Alerting: Incredibly powerful unsupervised machine learning intelligently readjusts time series models and uses automatic secondary checks to weed out false positives. -Time to Resolution: Automatically generates a root cause analysis that saves users time determining why an anomaly is occurring. Our triage feature orchestrates a resolution workflow and can integrate with many remediation steps, like ticketing systems. -In-VPC Development: Data never leaves the customer’s environment. Anomalo can be run entirely in-VPC for the utmost in privacy & security

In the current landscape, forward-thinking companies are utilizing data to outperform competitors, enhance customer satisfaction, and identify new avenues for growth. However, they also face the complexities posed by industry regulations and strict data privacy laws that put pressure on conventional technologies and workflows. The importance of data quality cannot be overstated, yet it frequently falters before reaching business intelligence and analytics tools. Wiiisdom Ops is designed to help organizations maintain quality assurance within the analytics phase, which is crucial for the final leg of the data journey. Neglecting this aspect could expose your organization to significant risks, leading to poor choices and potential automated failures. Achieving large-scale BI testing is unfeasible without the aid of automation. Wiiisdom Ops seamlessly integrates into your CI/CD pipeline, providing a comprehensive analytics testing loop while reducing expenses. Notably, it does not necessitate engineering expertise for implementation. You can centralize and automate your testing procedures through an intuitive user interface, making it easy to share results across teams, which enhances collaboration and transparency.

In 30 minutes, you can monitor your entire warehouse. Automated warehouse-to-BI lineage can identify downstream impacts. Trust can be lost in seconds and regained in months. With modern data-era observability, you can have peace of mind. It can be difficult to get the coverage you need with code-based tests. They take hours to create and maintain. Metaplane allows you to add hundreds of tests in minutes. Foundational tests (e.g. We support foundational tests (e.g. row counts, freshness and schema drift), more complicated tests (distribution shifts, nullness shiftings, enum modifications), custom SQL, as well as everything in between. Manual thresholds can take a while to set and quickly become outdated as your data changes. Our anomaly detection algorithms use historical metadata to detect outliers. To minimize alert fatigue, monitor what is important, while also taking into account seasonality, trends and feedback from your team. You can also override manual thresholds.

Create a scalable architecture that treats data products as first-class citizens. Automate and repurpose data products. Enable compliance and robust data governance. Control the costs of your data products and pipelines for Snowflake. This global pharmaceutical giant's data product teams can benefit from next-generation analytics using self-service data and analytics infrastructure that includes Snowflake and other tools that use a data mesh approach. The DataOps.live platform allows them to organize and benefit from next generation analytics. DataOps is a unique way for development teams to work together around data in order to achieve rapid results and improve customer service. Data warehousing has never been paired with agility. DataOps is able to change all of this. Governance of data assets is crucial, but it can be a barrier to agility. Dataops enables agility and increases governance. DataOps does not refer to technology; it is a way of thinking.

A low-code, no-code strategy enhances data quality management. This software-as-a-service (SaaS) model offers flexibility, cost-effectiveness, seamless integration, and robust support options. It maintains rigorous standards for encryption, identity management, role-based access control, data governance, and compliance. Utilizing advanced machine learning algorithms, it identifies anomalies in row-value data, with the capability to evolve alongside the unique requirements of users' businesses and datasets. Users can incorporate numerous data sources, records, and attributes effortlessly, making the platform resilient to unexpected increases in data volume. It accommodates both batch and streaming processing, ensuring that data is consistently monitored to provide real-time alerts without affecting pipeline performance. The platform offers a smooth onboarding, integration, and investigation process, making it accessible to data teams aiming to proactively spot and analyze anomalies as they arise. With a no-code onboarding process, users can simply connect to their data sources and set their alerting preferences. Telmai intelligently adapts to data patterns, notifying users of any significant changes, ensuring that they remain informed and prepared for any data fluctuations.

Empower your enterprise data teams to effectively avert expensive outages before they happen. Rapidly expand data quality assessments across your enterprise data pipelines using streamlined, time-sensitive pushdown queries that maintain performance standards. Proactively supervise and detect data anomalies by utilizing pre-built AI models tailored for data quality, eliminating the need for manual threshold adjustments. Lightup’s ready-to-use solution ensures your data maintains optimal health, allowing for assured business decision-making. Equip stakeholders with insightful data quality intelligence to back their choices with confidence. Feature-rich, adaptable dashboards offer clear visibility into data quality and emerging trends, fostering a better understanding of your data landscape. Prevent data silos by leveraging Lightup's integrated connectors, which facilitate seamless connections to any data source within your stack. Enhance efficiency by substituting laborious, manual processes with automated data quality checks that are both precise and dependable, thus streamlining workflows and improving overall productivity. With these capabilities in place, organizations can better position themselves to respond to evolving data challenges and seize new opportunities.

Detect and address code and optimization challenges in real-time, mitigate data incidents before deployment, and oversee data-affecting code modifications comprehensively—from the operational database to the user interface dashboard. With automated, column-level data lineage tracing the journey from the operational database to the reporting layer, every dependency is meticulously examined. Foundational automates the enforcement of data contracts by scrutinizing each repository in both upstream and downstream directions, directly from the source code. Leverage Foundational to proactively uncover code and data-related issues, prevent potential problems, and establish necessary controls and guardrails. Moreover, implementing Foundational can be achieved in mere minutes without necessitating any alterations to the existing codebase, making it an efficient solution for organizations. This streamlined setup promotes quicker response times to data governance challenges.

DataTrust is designed to speed up testing phases and lower delivery costs by facilitating continuous integration and continuous deployment (CI/CD) of data. It provides a comprehensive suite for data observability, validation, and reconciliation at an extensive scale, all without the need for coding and with user-friendly features. Users can conduct comparisons, validate data, and perform reconciliations using reusable scenarios. The platform automates testing processes and sends alerts when problems occur. It includes interactive executive reports that deliver insights into quality dimensions, alongside personalized drill-down reports equipped with filters. Additionally, it allows for comparison of row counts at various schema levels across multiple tables and enables checksum data comparisons. The rapid generation of business rules through machine learning adds to its versatility, giving users the option to accept, modify, or discard rules as required. It also facilitates the reconciliation of data from multiple sources, providing a complete array of tools to analyze both source and target datasets effectively. Overall, DataTrust stands out as a powerful solution for enhancing data management practices across different organizations.

Keep a close eye on your data health and the performance of your pipelines. Achieve comprehensive oversight for pipelines utilizing cloud-native technologies such as Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. This observability platform is specifically designed for Data Engineers. As the challenges in data engineering continue to escalate due to increasing demands from business stakeholders, Databand offers a solution to help you keep pace. With the rise in the number of pipelines comes greater complexity. Data engineers are now handling more intricate infrastructures than they ever have before while also aiming for quicker release cycles. This environment makes it increasingly difficult to pinpoint the reasons behind process failures, delays, and the impact of modifications on data output quality. Consequently, data consumers often find themselves frustrated by inconsistent results, subpar model performance, and slow data delivery. A lack of clarity regarding the data being provided or the origins of failures fosters ongoing distrust. Furthermore, pipeline logs, errors, and data quality metrics are often gathered and stored in separate, isolated systems, complicating the troubleshooting process. To address these issues effectively, a unified observability approach is essential for enhancing trust and performance in data operations.

Acceldata stands out as the sole Data Observability platform that offers total oversight of enterprise data systems, delivering extensive visibility into intricate and interconnected data architectures. It integrates signals from various workloads, as well as data quality, infrastructure, and security aspects, thereby enhancing both data processing and operational efficiency. With its automated end-to-end data quality monitoring, it effectively manages the challenges posed by rapidly changing datasets. Acceldata also provides a unified view to anticipate, detect, and resolve data-related issues in real-time. Users can monitor the flow of business data seamlessly and reveal anomalies within interconnected data pipelines, ensuring a more reliable data ecosystem. This holistic approach not only streamlines data management but also empowers organizations to make informed decisions based on accurate insights.