Telmai Alternatives

(Bank CFO) “I don’t have confidence and trust in our data. We keep discovering hidden risks”. Since 70% of data initiatives fail due to unreliable data (Gartner research), are you risking your reputation by trusting the accuracy of your data that you share with your business stakeholders and partners? Data Trust Scores must be measured in Data Lakes, warehouses, and throughout the pipeline, to ensure the data is trustworthy and fit for use. It typically takes 4-6 weeks of manual effort just to set a file or table for validation. Then, the rules have to be constantly updated as the data evolves. The only scalable option is to automate data validation rules discovery and rules maintenance. DataBuck is an autonomous, self-learning, Data Observability, Quality, Trustability and Data Matching tool. It reduces effort by 90% and errors by 70%. "What took my team of 10 Engineers 2 years to do, DataBuck could complete it in less than 8 hours." (VP, Enterprise Data Office, a US bank)

Monitor your entire warehouse in 30 minutes. Identify downstream impact with automated warehouse-to-BI lineage. Trust takes seconds to lose and months to regain. Gain peace of mind with observability built for the modern data era. Code-based tests take hours to write and maintain, so it's hard to achieve the coverage you need. In Metaplane, you can add hundreds of tests within minutes. We support foundational tests (e.g. row counts, freshness, and schema drift), more complex tests (distribution drift, nullness shifts, enum changes), custom SQL, and everything in between. Manual thresholds take a long time to set and quickly go stale as your data changes. Our anomaly detection models learn from historical metadata to automatically detect outliers. Monitor what matters, all while accounting for seasonality, trends, and feedback from your team to minimize alert fatigue. Of course, you can override with manual thresholds, too.

Automatically cover thousands of tables with ML-based anomaly detection and 50+ custom metrics. Comprehensive data and metadata monitoring. Exhaustive mapping of all dependencies between assets, from ingestion to BI. Enhanced productivity and collaboration between data engineers and data consumers. Sifflet seamlessly integrates into your data sources and preferred tools and can run on AWS, Google Cloud Platform, and Microsoft Azure. Keep an eye on the health of your data and alert the team when quality criteria aren’t met. Set up in a few clicks the fundamental coverage of all your tables. Configure the frequency of runs, their criticality, and even customized notifications at the same time. Leverage ML-based rules to detect any anomaly in your data. No need for an initial configuration. A unique model for each rule learns from historical data and from user feedback. Complement the automated rules with a library of 50+ templates that can be applied to any asset.

Prevent data outages by identifying and fixing data quality issues before they get into production. Go from 0 to 100% test coverage of your data pipelines in a day. Know the impact of each code change with automatic regression testing across billions of rows. Automate change management, improve data literacy, achieve compliance, and reduce incident response time. Don’t let data incidents take you by surprise. Be the first one to know with automated anomaly detection. Datafold’s easily adjustable ML model adapts to seasonality and trend patterns in your data to construct dynamic thresholds. Save hours spent on trying to understand data. Use the Data Catalog to find relevant datasets, fields, and explore distributions easily with an intuitive UI. Get interactive full-text search, data profiling, and consolidation of metadata in one place.

Empower enterprise data teams to proactively prevent costly outages, before they occur. Quickly scale data quality checks across enterprise data pipelines with efficient time-bound pushdown queries — without compromising performance. Proactively monitor and identify data anomalies, leveraging prebuilt DQ-specific AI models — without manual threshold setting. Lightup’s out-of-the-box solution gives you the highest level of data health so you can make confident business decisions. Arm stakeholders with data quality intelligence for confident decision-making. Powerful, flexible dashboards provide transparency into data quality and trends. Avoid data silos by using Lightup’s built-in connectors to seamlessly connect to any data source in your data stack. Streamline workflows by replacing manual, resource-intensive processes with automated and accurate data quality checks.

HighByte Intelligence Hub is the first DataOps solution purpose-built for industrial data. It provides manufacturers with a low-code software solution to accelerate and scale the usage of operational data throughout the extended enterprise by contextualizing, standardizing, and securing this valuable information. HighByte Intelligence Hub runs at the Edge, scales from embedded to server-grade computing platforms, connects devices and applications via a wide range of open standards and native connections, processes streaming data through standard models, and delivers contextualized and correlated information to the applications that require it. Use HighByte Intelligence Hub to reduce system integration time from months to hours, accelerate data curation and preparation for AI and ML applications, improve system-wide security and data governance, and reduce Cloud ingest, processing, and storage costs and complexity. Build a digital infrastructure that is ready for scale.

The ultimate platform for expanding your business horizons with data-driven decisions. Improve every step of your supply chain journey. Our no-code platform enhances the quality of master data to offer you a set of optimization solutions, from inventory planning to distribution network. Relying on trusted data-driven analytics, you can proactively prevent critical issues from arising, making crucial real-time adjustments. Build trust in your data and manage them with confidence. Our user-friendly platform empowers financial institutions with transparent data-driven insights to improve key financial processes. We put eXplainable AI in the hands of business experts, so they can develop advanced financial models and improve decision-making. Rulex Academy will teach you all you need to know to analyse your data, build your first workflows, get to grips with algorithms, and quickly optimize complex processes with our self-paced, interactive online training courses.

Talend Data Fabric’s suite of cloud services efficiently handles all your integration and integrity challenges — on-premises or in the cloud, any source, any endpoint. Deliver trusted data at the moment you need it — for every user, every time. Ingest and integrate data, applications, files, events and APIs from any source or endpoint to any location, on-premise and in the cloud, easier and faster with an intuitive interface and no coding. Embed quality into data management and guarantee ironclad regulatory compliance with a thoroughly collaborative, pervasive and cohesive approach to data governance. Make the most informed decisions based on high quality, trustworthy data derived from batch and real-time processing and bolstered with market-leading data cleaning and enrichment tools. Get more value from your data by making it available internally and externally. Extensive self-service capabilities make building APIs easy— improve customer engagement.

Rapidly transform high-volume, disconnected data into trusted and actionable business insights with scalable enterprise data quality. Trillium Quality is a versatile, powerful data quality solution that supports your rapidly changing business needs, data sources and enterprise infrastructures – including big data and cloud. Its data cleansing and standardization features automatically understand global data, such as customer, product and financial data, in any context – making pre-formatting and pre-processing unnecessary. Trillium Quality services deploy in batch or in real-time, on-premises or in the cloud, using the same rule sets and standards across an unlimited number of applications and systems. Open APIs let you seamlessly connect to custom and third-party applications, while controlling and managing data quality services centrally from one location.

Helping enterprises proactively manage their full data quality lifecycle through contextual data quality checks, anomaly detection and remediation. Expose anomalies and metadata to help teams take corrective actions. Automatically trigger remediation workflows to resolve errors quickly and efficiently. Maintain high data quality and prevent errors from affecting business decisions. The SLA chart provides an overview of SLA, including the total number of SLA monitoring that have been performed and any violations that have occurred. This chart can help you identify areas of your data that may require further investigation or improvement.

The only Data Observability platform that provides complete control of enterprise data systems. Provides comprehensive, cross-sectional visibility into complex, interconnected data systems. Synthesizes signals across workloads, data quality, infrastructure and security. Improves data processing and operational efficiency. Automates end-to-end data quality monitoring for fast-changing, mutable datasets. Acceldata provides a single pane of glass to help predict, identify, and fix data issues. Fix complete data issues in real-time. Observe business data flow from a single pane of glass. Uncover anomalies across interconnected data pipelines.

An AI-powered data management platform that enables true data democratization. Integrates & centralizes all data sources, facilitates collaboration, and empowers organizations for innovation, driven by Insights. SCIKIQ is a holistic business data platform that simplifies data complexities from business users through a no-code, drag-and-drop user interface which allows businesses to focus on driving value from data, thereby enabling them to grow, and make faster and smarter decisions with confidence. Use box integration, connect any data source, and ingest any structured and unstructured data. Build for business users, ease of use, a simple no-code platform, and use drag and drop to manage your data. Self-learning platform. Cloud agnostic, environment agnostic. Build on top of any data environment. SCIKIQ architecture is designed specifically to address the challenges facing the complex hybrid data landscape.

We are a leader in Data Quality & ML Model for enterprises adopting a multi-cloud, ML and modern data management ecosystem. Algorithms to track Data Anomalies in Azure, GCP & AWS databases. Measure and monitor data issues from all your cloud database management tools and data silos, using a single, centralized tool. Quality is in the eye of the beholder. Data issues have different implications depending on where you sit in the enterprise. Qualdo is a pioneer in organizing all data quality management issues through the lens of multiple enterprise stakeholders, presenting a unified view in a consumable format. Deploy powerful auto-resolution algorithms to track and isolate critical data issues. Take advantage of robust reports and alerts to manage your enterprise regulatory compliance.

Digna is an AI-powered anomaly detection solution designed to meet the challenges of modern data quality management. It's domain agnostic, meaning it seamlessly adapts to various sectors, from finance to healthcare. Digna prioritizes data privacy, ensuring compliance with stringent data regulations. Moreover, it's built to scale, growing alongside your data infrastructure. With the flexibility to choose cloud-based or on-premises installation, Digna aligns with your organizational needs and security policies. In conclusion, Digna stands at the forefront of modern data quality solutions. Its user-friendly interface, combined with powerful AI-driven analytics, makes it an ideal choice for businesses seeking to improve their data quality. With its seamless integration, real-time monitoring, and adaptability, Digna is not just a tool; it’s a partner in your journey towards impeccable data quality.

Native to Azure, DQ on Demand™ is architected to provide incredible performance and scalability. Switch data providers with ease and enhance your customer data on a pay-as-you-go basis by plugging straight into our DQ on Demand™ web services, providing you with an easy-to-access data quality marketplace. Many data services are available including data cleansing, enrichment, formatting, validation, verification, data transformations, and many more. Simply connect to our web-based APIs. Switch data providers with ease, giving you ultimate flexibility. Benefit from complete developer documentation. Only pay for what you use. Purchase credits and apply them to whatever service you require. Easy to set up and use. Expose all of our DQ on Demand™ functions right within Excel for a familiar, easy-to-use low-code no-code solution. Ensure your data is cleansed right within MS Dynamics with our DQ PCF controls.

AI-powered data integration tool that helps streamline the process of customer data onboarding. It allows for easy and fast automated data integration from various sources without coding, reducing preparation time to just a few minutes. With Datuum, organizations can efficiently extract, ingest, transform, migrate, and establish a single source of truth for their data, while integrating it into their existing data storage. Datuum is a no-code product and can reduce up to 80% of the time spent on data-related tasks, freeing up time for organizations to focus on generating insights and improving the customer experience. With over 40 years of experience in data management and operations, we at Datuum have incorporated our expertise into the core of our product, addressing the key challenges faced by data engineers and managers and ensuring that the platform is user-friendly, even for non-technical specialists.

Your zero-touch copilot for data quality, spending, performance, and usage. Your data team won’t be the last to know about broken analytics or bottlenecks. We pull out anomalies and alert you right away. Improve your data quality and eliminate downtimes. When performance trends the wrong way, you’ll be the first to know. We help you connect the dots between data usage and resource allocation. Reduce and optimize costs, and allocate resources effectively. We slice and dice your spending areas by warehouse, user, and query. When spending trends the wrong way, you get a notification. Get insights on underutilized data and its impact on your business value. Revefi constantly watches out for waste and surfaces opportunities for you to better rationalize usage with resources. Say goodbye to manual data checks with automated monitoring built on your data warehouse. You can find the root cause and solve issues within minutes before they affect your downstream users.

Anomalo helps you get ahead of data issues by automatically detecting them as soon as they appear in your data and before anyone else is impacted. Detect, root-cause, and resolve issues quickly – allowing everyone to feel confident in the data driving your business. Connect Anomalo to your Enterprise Data Warehouse and begin monitoring the tables you care about within minutes. Our advanced machine learning will automatically learn the historical structure and patterns of your data, allowing us to alert you to many issues without the need to create rules or set thresholds.‍ You can also fine-tune and direct our monitoring in a couple of clicks via Anomalo’s No Code UI. Detecting an issue is not enough. Anomalo’s alerts offer rich visualizations and statistical summaries of what’s happening to allow you to quickly understand the magnitude and implications of the problem.‍

Adopting data-centric AI has never been easier with automated data quality profiling and synthetic data generation. We help data scientists to unlock data's full potential. YData Fabric empowers users to easily understand and manage data assets, synthetic data for fast data access, and pipelines for iterative and scalable flows. Better data, and more reliable models delivered at scale. Automate data profiling for simple and fast exploratory data analysis. Upload and connect to your datasets through an easily configurable interface. Generate synthetic data that mimics the statistical properties and behavior of the real data. Protect your sensitive data, augment your datasets, and improve the efficiency of your models by replacing real data or enriching it with synthetic data. Refine and improve processes with pipelines, consume the data, clean it, transform your data, and work its quality to boost machine learning models' performance.

CLEAN_Data is a collection of enterprise data quality solutions for managing the challenging and ever changing profiles of employee, customer, vendor, student, and alumni contact data. Our CLEAN_Data solutions are crucial in managing your enterprise data integrity requirements. Whether you are processing your data in real-time, batch, or connecting data systems, Runner EDQ has an integrated data solution your organization can rely on. CLEAN_Address is the integrated address verification solution that corrects and standardizes postal addresses within Oracle®, Ellucian® and other enterprise systems (ERP, SIS, HCM, CRM, MDM). Our seamless integration provides address correction in real-time at the point of entry and for existing data via batch and change of address processing. Real time address verification in all address entry pages using native fields in your SIS or CRM. Integrated batch processing corrects and formats your existing address records.

Identify code and optimization issues in real-time, prevent data incidents pre-deploy, and govern data-impacting code changes end to end—from the operational database to the user-facing dashboard. Automated, column-level data lineage, from the operational database all the way to the reporting layer, ensures every dependency is analyzed. Foundational automates data contract enforcement by analyzing every repository from upstream to downstream, directly from source code. Use Foundational to proactively identify code and data issues, find and prevent issues, and create controls and guardrails. Foundational can be set up in minutes with no code changes required.

Data is used in every aspect of a processing plant or facility, it is underlying most operational processes, most business decisions, and most environmental events. Failures are often attributed to this same data, in terms of operator error, bad sensors, safety or environmental events, or poor analytics. This is where APERIO can alleviate these problems. Data integrity is a key element of Industry 4.0; the foundation upon which more advanced applications, such as predictive models, process optimization, and custom AI tools are developed. APERIO DataWise is the industry-leading provider of reliable, trusted data. Automate the quality of your PI data or digital twins continuously and at scale. Ensure validated data across the enterprise to improve asset reliability. Empower the operator to make better decisions. Detect threats made to operational data to ensure operational resilience. Accurately monitor & report sustainability metrics.

Find out why the heavy hitters are using the Crux external data automation platform to scale external data integration, transformation, and observability without increasing headcount. Our cloud-native data integration technology accelerates the ingestion, preparation, observability and ongoing delivery of any external dataset. The result is that we can ensure you get quality data in the right place, in the right format when you need it. Leverage automatic schema detection, delivery schedule inference, and lifecycle management to build pipelines from any external data source quickly. Enhance discoverability throughout your organization through a private catalog of linked and matched data products. Enrich, validate, and transform any dataset to quickly combine it with other data sources and accelerate analytics.

Decube is a data management platform that helps organizations manage their data observability, data catalog, and data governance needs. It provides end-to-end visibility into data and ensures its accuracy, consistency, and trustworthiness. Decube's platform includes data observability, a data catalog, and data governance components that work together to provide a comprehensive solution. The data observability tools enable real-time monitoring and detection of data incidents, while the data catalog provides a centralized repository for data assets, making it easier to manage and govern data usage and access. The data governance tools provide robust access controls, audit reports, and data lineage tracking to demonstrate compliance with regulatory requirements. Decube's platform is customizable and scalable, making it easy for organizations to tailor it to meet their specific data management needs and manage data across different systems, data sources, and departments.

DQOps is an open-source data quality platform designed for data quality and data engineering teams that makes data quality visible to business sponsors. The platform provides an efficient user interface to quickly add data sources, configure data quality checks, and manage issues. DQOps comes with over 150 built-in data quality checks, but you can also design custom checks to detect any business-relevant data quality issues. The platform supports incremental data quality monitoring to support analyzing data quality of very big tables. Track data quality KPI scores using our built-in or custom dashboards to show progress in improving data quality to business sponsors. DQOps is DevOps-friendly, allowing you to define data quality definitions in YAML files stored in Git, run data quality checks directly from your data pipelines, or automate any action with a Python Client. DQOps works locally or as a SaaS platform.

Snowplow is a best-in-class data collection platform built for Data Teams. With Snowplow you can collect rich, high-quality event data from all your platforms and products. Your data is available in real-time and is delivered to your data warehouse of choice where it can easily be joined with other data sets and used to power BI tools, custom reports or machine learning models. The Snowplow pipeline runs in your cloud account (AWS and/or GCP), giving you complete ownership of your data. Snowplow frees you to ask and answer any questions relevant to your business and use case, using your preferred tools and technologies.

What is Melissa Clean Suite? Melissa’s Clean Suite (previously Melissa Listware) fights dirty data in your Salesforce®, Microsoft Dynamics CRM®, or Oracle CRM and ERP platforms by verifying, standardizing, correcting and appending your customer contact data records. The result – clean, vibrant, valuable data you can use for squeaky clean omnichannel marketing and sales success. • Autocomplete, verify and correct contacts before they enter the CRM • Add valuable demographic and firmographic data for effective lead scoring, targeting and segmentation • Keep contacts clean and up-to-date for improved sales follow up and marketing initiatives •Protect the quality of your customer data with real-time, point of entry data cleansing or batch processing Data drives every aspect of customer communication, decision making, analytics and strategy. But, dirty data – stale, incorrect or incomplete data – leads to an inaccurate view of your customers, inefficient operations

Experian Data Quality is a recognized industry leader of data quality and data quality management solutions. Our comprehensive solutions validate, standardize, enrich, profile, and monitor your customer data so that it is fit for purpose. With flexible SaaS and on-premise deployment models, our software is customizable to every environment and any vision. Keep address data up to date and maintain the integrity of contact information over time with real-time address verification solutions. Analyze, transform, and control your data using comprehensive data quality management solutions - develop data processing rules that are unique to your business. Improve mobile/SMS marketing efforts and connect with customers using phone validation tools from Experian Data Quality.

NetOwl NameMatcher, the winner of the MITRE Multicultural Name Matching Challenge, offers the most accurate, fast, and scalable name matching available. Using a revolutionary machine learning-based approach, NetOwl addresses complex fuzzy name matching challenges. Traditional name matching approaches, such as Soundex, edit distance, and rule-based methods, suffer from both precision (false positives) and recall (false negative) problems in addressing the variety of fuzzy name matching challenges discussed above. NetOwl applies an empirically driven, machine learning-based probabilistic approach to name matching challenges. It derives intelligent, probabilistic name matching rules automatically from large-scale, real-world, multi-ethnicity name variant data. NetOwl utilizes different matching models optimized for each of the entity types (e.g., person, organization, place) In addition, NetOwl performs automatic name ethnicity detection as well.

See how your data assets are used: popularity, utilization, and schema coverage. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Find and filter the data you need based on metadata tags and descriptions. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Drive data governance and ownership across your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Automatically generated field-level lineage map to understand the entire data ecosystem. Anomaly detection learns from your data and seasonality patterns, with automatic backfill from historical data. Machine learning-based thresholds are trained per data segment, trained on actual data instead of metadata only.

accel-DS is one and only such tool that can get you going today, with its zero coding, drag and drop technology. As you build your data set, see results interactively in a familiar Spreadsheet like interface! Use the same Spreadsheet to apply data cleansing Transformations. This innovative solution breaks the Write Code to Extract, Transform, Load and finally View Results traditional ETL development cycle. Built for Business / End Users from grounds up. Integrate data from any Database, XML, JSON, WSDL, Streams (Twitter, Sys Log). No coding needed, just drag & drop your data sources. Built grounds up for Big Data, ingest, cleanse and transform data from any data source into Hadoop / Big Data easily. Loads GBs of data from RDBMS and Files into Big Data in minutes. Traditional data types and complex data types such as Maps, Structures are supported as well.

SAS Data Quality meets you where you are, addressing your data quality issues without requiring you to move your data. You’ll work faster and more efficiently – and, with role-based security, you won’t put sensitive data at risk. Data quality isn’t something you do just once; it’s a process. We help you at every stage, making it easy to profile and identify problems, preview data, and set up repeatable processes to maintain a high level of data quality. Only SAS delivers this much breadth and depth of data quality knowledge. We’ve experienced it all – and integrated that experience into our products. We know that data quality can mean taking things that look wrong and seeing if they’re actually right. How? With matching logic. Profiling. Deduplicating. SAS Data Quality gives business users the power to update and tweak data themselves, so IT is no longer spread too thin. Out-of-the-box capabilities don’t require extra coding.

DataMatch Enterprise™ solution is a highly visual data cleansing application specifically designed to resolve customer and contact data quality issues. The platform leverages multiple proprietary and standard algorithms to identify phonetic, fuzzy, miskeyed, abbreviated, and domain-specific variations. Build scalable configurations for deduplication & record linkage, suppression, enhancement, extraction, and standardization of business and customer data and create a Single Source of Truth to maximize the impact of your data across the enterprise.

Our solutions monitor your data around the clock to detect any potential issues in the quality of your data and its integration with other internal systems, so your bottom line isn’t impacted in any way. Ensure your data is 100% accurate before it’s transferred or shared between your systems. If something doesn’t look right, you’ll be notified immediately and that data pipeline will be stopped until the issue is resolved. We enable our customers to be regulatory compliant from a data standpoint by ensuring our data solutions adhere to and support specific governance policies based on your industry and the regions you work within. We empower our customers to gain greater control over their data sets by showing them that it can be easy to measure and meet their data goals and requirements, by leveraging our simple user interface.

Cleanlab Studio handles the entire data quality and data-centric AI pipeline in a single framework for analytics and machine learning tasks. Automated pipeline does all ML for you: data preprocessing, foundation model fine-tuning, hyperparameter tuning, and model selection. ML models are used to diagnose data issues, and then can be re-trained on your corrected dataset with one click. Explore the entire heatmap of suggested corrections for all classes in your dataset. Cleanlab Studio provides all of this information and more for free as soon as you upload your dataset. Cleanlab Studio comes pre-loaded with several demo datasets and projects, so you can check those out in your account after signing in.

Monitor your data health and pipeline performance. Gain unified visibility for pipelines running on cloud-native tools like Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. An observability platform purpose built for Data Engineers. Data engineering is only getting more challenging as demands from business stakeholders grow. Databand can help you catch up. More pipelines, more complexity. Data engineers are working with more complex infrastructure than ever and pushing higher speeds of release. It’s harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs. Data consumers are frustrated with inconsistent results, model performance, and delays in data delivery. Not knowing exactly what data is being delivered, or precisely where failures are coming from, leads to persistent lack of trust. Pipeline logs, errors, and data quality metrics are captured and stored in independent, isolated systems.

TYPO is a data quality solution that provides error correction at the point of entry into information systems. Unlike reactive data quality tools that attempt to resolve data errors after they are saved, Typo uses AI to proactively detect errors in real-time at the initial point of entry. This enables immediate correction of errors prior to storage and propagation into downstream systems and reports. Typo can be used on web applications, mobile apps, devices and data integration tools. Typo inspects data in motion as it enters your enterprise or at rest after storage. Typo provides comprehensive oversight of data origins and points of entry into information systems including devices, APIs and application users. When an error is identified, the user is notified and given the opportunity to correct the error. Typo uses machine learning algorithms to detect errors. Implementation and maintenance of data rules is not necessary.

Whether you’re preparing for a data migration, looking to achieve reliable customer insight, or complying with regulation, you can rely on our data quality management solutions. With Experian, it means powerful data profiling, data discovery, data cleansing and enrichment, process orchestration, and the ability to run full-volume analyses, among other things. Getting insight into your business’s data is now easier and faster than ever before. Our solutions allow you to seamlessly connect to hundreds of data sources to remove duplicates, correct errors, and standardize formats. With improved data quality, comes a more comprehensive view of your customers, business operations, and more.

The open-source ML observability platform. Evaluate, test, and monitor ML models from validation to production. From tabular data to NLP and LLM. Built for data scientists and ML engineers. All you need to reliably run ML systems in production. Start with simple ad hoc checks. Scale to the complete monitoring platform. All within one tool, with consistent API and metrics. Useful, beautiful, and shareable. Get a comprehensive view of data and ML model quality to explore and debug. Takes a minute to start. Test before you ship, validate in production and run checks at every model update. Skip the manual setup by generating test conditions from a reference dataset. Monitor every aspect of your data, models, and test results. Proactively catch and resolve production model issues, ensure optimal performance, and continuously improve it.

Extract, normalize, and standardize your data across multiple inputs and formats. Normalize all your information – including business and individual data, structured and unstructured. Precisely applies supervised machine learning neural network-based techniques to understand the structure and variations of different types of information and parses data automatically. Spectrum Quality is ideally suited for global client bases that require multi-level data standardization and transliteration for multiple languages and culturally specific terms, including those in Arabic, Chinese, Japanese and Korean. Our advanced text-processing enables information extraction from any natural language input text and assigns categories to unstructured text. Using pre-trained models and machine learning based algorithms, you can extract entities and further train and customize your models to define specific entities of any domain or type.

Maximize the value of all your organization’s structured and unstructured data with exceptional functionalities for data integration, quality, and cleansing. SAP Data Services software improves the quality of data across the enterprise. As part of the information management layer of SAP’s Business Technology Platform, it delivers trusted,relevant, and timely information to drive better business outcomes. Transform your data into a trusted, ever-ready resource for business insight and use it to streamline processes and maximize efficiency. Gain contextual insight and unlock the true value of your data by creating a complete view of your information with access to data of any size and from any source. Improve decision-making and operational efficiency by standardizing and matching data to reduce duplicates, identify relationships, and correct quality issues proactively. Unify critical data on premise, in the cloud, or within Big Data by using intuitive tools.

Unify your data catalog, reduce communication overhead and enable quality control to any member of your company, all without deploying or installing anything. rudol is a data quality platform that helps companies understand all their data sources, no matter where they come from; reduces excessive communication in reporting processes or urgencies; and enables data quality diagnosing and issue prevention to all the company, through easy steps With rudol, each organization is able to add data sources from a growing list of providers and BI tools with a standardized structure, including MySQL, PostgreSQL, Airflow, Redshift, Snowflake, Kafka, S3*, BigQuery*, MongoDB*, Tableau*, PowerBI*, Looker* (* in development). So, regardless of where it’s coming from, people can understand where and how the data is stored, read and collaborate with its documentation, or easily contact data owners using our integrations.

Profile, cleanse, match and deduplicate data in drag-and-drop rules studio. Lo-code UI means no programming skill required, putting power in the hands of subject matter experts. Add AI & machine learning to your existing data management processes In order to reduce manual effort and increase accuracy, providing full transparency on machine-led decisions with human-in-the-loop. Offering award-winning data quality and matching capabilities across multiple industries, our self-service solutions are rapidly configured within weeks with specialist assistance available from Datactics data engineers. With Datactics you can easily measure data to regulatory & industry standards, fix breaches in bulk and push into reporting tools, with full visibility and audit trail for Chief Risk Officers. Augment data matching into Legal Entity Masters for Client Lifecycle Management.

Easyence is the only Customer Infastructure dedicated to data-driven retailers. Join 240+ businesses that use Easyence Customer Data Platform and Apps to deliver memorable customer experience. Easyence collects customer events (products, stores, etc.), leverages your current models with smart algorithmes to serve your business, and provides a complete toolkit of applications to your marketing team. Know more about our Saas products • Easyence Data Platform : collect and unify your customers' events across every platform • Easyence Audience App : build audiences and create campaigns, measure your uplift without relying on other teams • Easyence E-Merchandising App : expose the right product to the right customer at right time. • Easyence Attribution App : unify your customer’s touch points across all platforms and channels. • Easyence Insight App: measure and analyze the value generated by omnicanality to understand consumers’ behaviors.

Great Expectations is a shared, open standard for data quality. It helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. We recommend deploying within a virtual environment. If you’re not familiar with pip, virtual environments, notebooks, or git, you may want to check out the Supporting. There are many amazing companies using great expectations these days. Check out some of our case studies with companies that we've worked closely with to understand how they are using great expectations in their data stack. Great expectations cloud is a fully managed SaaS offering. We're taking on new private alpha members for great expectations cloud, a fully managed SaaS offering. Alpha members get first access to new features and input to the roadmap.

Connect to your customers through better data. Clean, protect, and enhance your data with the industry’s most powerful data quality platform. RingLead Cleanse uses patented duplicate merging technology to detect and eliminate duplicates inside your CRM and MAP. Stop dirty data at the source with perimeter protection at all entry points into your CRM and MAP database. RingLead Route provides complete control and visibility over the lead-to-rep process with configurable workflows and a powerful rules engine to route all Salesforce objects. Assigning leads in a timely and accurate fashion continues to be a top priority, yet many organizations still rely on primitive approaches to routing. Leads get assigned to the wrong rep, qualified leads fall through the cracks, and conversion rates suffer.

Validate and verify your address data by checking them against official Postal Authority databases. Increase delivery rates, minimize returned mail and realize postal discounts. Connect address datasources to our enterprise-class cleansing transforms. Then, you'll be ready to validate and verify your address data. Increase delivery rates, minimize returned mail and realize postal discounts. Identify individual data elements within your address data and break them out into their component parts. Eliminate common spelling mistakes & format address data to comply with industry standards & improve mail delivery. Confirm an address’s existence against the official USPS address database. Check whether the address is residential or business and if the address is deliverable using USPS Delivery Point Validation (DPV). Merge validated data back to multiple disparate data sources or produce customized output files to use in your organization's workflow.

What is CoSort? IRI CoSort® is a fast, affordable, and easy-to-use sort/merge/report utility, and a full-featured data transformation and preparation package. The world's first sort product off the mainframe, CoSort continues to deliver maximum price-performance and functional versatility for the manipulation and blending of big data sources. CoSort also powers the IRI Voracity data management platform and many third-party tools. What does CoSort do? CoSort runs multi-threaded sort/merge jobs AND many other high-volume (big data) manipulations separately, or in combination. It can also cleanse, mask, convert, and report at the same time. Self-documenting 4GL scripts supported in Eclipse™ help you speed or leave legacy: sort, ETL and BI tools; COBOL and SQL programs, plus Hadoop, Perl, Python, and other batch jobs. Use CoSort to sort, join, aggregate, and load 2-20X faster than data wrangling and BI tools, 10x faster than SQL transforms, and 6x faster than most ETL tools.

Enterprise-grade architecture and cloud data platform powered by Snowflake® to securely store and leverage your data in the cloud. Built-in ETL and drag-and-drop visual workflow designer to connect, clean & transform your data from 250+ data sources. Use the latest in Search and AI-driven technology to generate insights and actionable analytics from your data in seconds. Leverage our AI/ML environments to build, tune and deploy your models for predictive analytics and forecasting. Leverage our built-in AI/ML environments to take your data to the next level. Create, train, tune and deploy your AI models for predictive analysis and forecasting, using the PurpleCube Data Science module. Build BI visualizations with PurpleCube Analytics, search through your data using natural language, and leverage AI-driven insights and smart suggestions that deliver answers to questions you didn’t think to ask.

We’ve built our analytics machine over 40 years and countless clients, constantly developing the most updated approach for the latest modern enterprise. Today, that means superior visualization, at-your-fingertips insights generation, and the ability to democratize access to data. The single-minded goal? To help you drive business results by enabling informed decision-making. A sophisticated data strategy only matters if the data that informs it is accessible. How exactly you see your data – its trends and patterns – determines how useful it can be. Empower your organization to make sound strategic decisions by employing real-time, customized, and self-service dashboards that bring that data to life. You don’t need to rely on gut feelings or, worse, wallow in ambiguity. Exceptional visualization and reporting allows your entire enterprise to organize around the same information and grow.