Alternatives to Revefi Data Operations Cloud

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.

OpenDQ is a zero-cost enterprise data quality, master and governance solution. OpenDQ is modularly built and can scale to meet your enterprise data management requirements. OpenDQ provides trusted data using a machine learning- and artificial intelligence-based framework. Comprehensive Data Quality Matching Profiling Data/Address Standardization Master Data Management 360 View of Customer Data Governance Business Glossary Meta Data Management

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 Manual thresholds can take a while to set and quickly become outdated as your data changes.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.

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.

You can prevent data outages by identifying data quality issues and fixing them before they reach production. In less than a day, you can increase your test coverage for data pipelines from 0 to 100%. Automatic regression testing across billions upon billions of rows allows you to determine the impact of every code change. Automate change management, improve data literacy and compliance, and reduce incident response times. Don't be taken by surprise by data incidents. Automated anomaly detection allows you to be the first to know about them. Datafold's ML model, which can be easily adjusted by Datafold, adapts to seasonality or trend patterns in your data to create dynamic thresholds. You can save hours trying to understand data. The Data Catalog makes it easy to search for relevant data, fields, or explore distributions with an intuitive UI. Interactive full-text search, data profiling and consolidation of metadata all in one place.

Empower enterprise data teams with the ability to prevent costly outages before they happen. With efficient time-bound queries, you can quickly scale data quality checks throughout enterprise data pipelines without compromising performance. Utilizing AI models that are specific to DQ, you can monitor and identify data anomalies without having to manually set thresholds. Lightup's solution provides you with the highest level of data quality so you can make confident decisions. Data quality intelligence will help you make confident decisions. Dashboards that are flexible and powerful provide transparency on data quality and trends. Lightup's built in connectors allow you to connect seamlessly to any data source within your data stack. Replace manual, resource-intensive data quality checks with automated ones to streamline workflows.

Enterprises can manage their data quality lifecycle proactively through contextual data checks, anomaly detection, and remediation. Expose anomalies, metadata and help teams take corrective action. Automate remediation workflows for quick and efficient error resolution. Maintain high data-quality and prevent errors from impacting business decisions. The SLA chart gives an overview of SLA. It includes the total number SLA monitoring performed and any violations. This chart will help you identify data areas that require further investigation or improvements.

Automates data cleansing & consolidates data into a clean, trustworthy data layer to feed downstream reporting. Manages suppliers' data requests. Monitors data workflow to identify bottlenecks and resolve problems. To prove quality assurance for each data row, creates an audit trail. You can customize validation and governance to fit your organization. Data analysts can focus on their insights by reducing data prep time by 60% The central KPI Dashboard provides key metrics about your data pipeline. This allows you to identify bottlenecks and resolve issues, as well as improve performance. Flexible rules engine allow users to create validation and testing that are tailored to their needs. It's easy to integrate gather360 into your existing tools or use it for setting up your cloud infrastructure.

SAS Data Quality is available to you wherever you are. It addresses your data quality issues without you having to move your data. You will work faster and more efficiently, and sensitive data won't be at risk with role-based security. Data quality is not something you do once. It's a process. We can help you at each stage. It's easy to identify and fix problems, preview data and set up repeatable processes that will ensure data quality. SAS is the only company that can provide this level of data quality knowledge. SAS has been there and done it all. We have incorporated that experience into our products. Data quality can be as simple as looking at things wrongly and then confirming that they are correct. How? With matching logic. Profiling. Deduplicating. SAS Data Quality gives business users the ability to update and modify data, so IT is not spread too thin. Out-of-the-box capabilities don't require extra coding.

Get a clear view of your data assets: popularity, usage, and schema coverage. Get important insights into your data assets, such as popularity and utilization. Find and filter data based on tags and descriptions in metadata. Get valuable insights about your data assets, such as popularity, usage, quality, and schema cover. Drive data governance and ownership throughout your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Lineage maps are automatically generated at the field level to help understand the entire data ecosystem. Anomaly detection is based on your data and seasonality patterns. It uses automatic backfilling from historical data. Machine learning thresholds are trained for each data segment and not just metadata.

It is important to understand the quality, structure, and content of your data before making any business decisions. IBM® InfoSphere® Information Analyzer is a component to IBM InfoSphere Information Server that evaluates data structure and quality within and across heterogeneous environments. It uses a reusable rule library and supports multilevel evaluations by pattern and rule record. It allows you to manage exceptions to existing rules and helps you identify data inconsistencies, redundancies and anomalies.

TYPO is a data-quality solution that corrects errors at the point of entry to information systems. Typo uses AI to detect errors at the point of entry, rather than reactive tools that try to fix data errors after they have been saved. This allows for immediate corrections before they are stored and propagated into downstream systems and reports. Typo can be used in web apps, mobile apps, devices, and data integration tools. Typo can inspect data in motion as it enters an enterprise or at rest after storage. Typo provides complete oversight of data origins, points of entry and exit into information systems, including devices and APIs. The user is notified when an error is detected and given the chance to correct it. Typo uses machine learning algorithms for detecting errors. It is not necessary to implement and maintain data rules.

Automate the automatic coverage of thousands of tables using ML-based anomaly detection. 50+ custom metrics are also available. Monitoring of metadata and data. Comprehensive mapping of all dependencies between assets from ingestion to reporting. Collaboration between data consumers and data engineers is enhanced and productivity is increased. Sifflet integrates seamlessly with your data sources and preferred tools. It can run on AWS and Google Cloud Platform as well as Microsoft Azure. Keep an eye on your data's health and notify the team if quality criteria are not being met. In a matter of seconds, you can set up the basic coverage of all your tables. You can set the frequency, criticality, and even custom notifications. Use ML-based rules for any anomaly in your data. There is no need to create a new configuration. Each rule is unique because it learns from historical data as well as user feedback. A library of 50+ templates can be used to complement the automated rules.

A low-code no-code approach to data quality. SaaS offers flexibility, affordability, ease-of-integration, and efficient support. High standards for encryption, identity management and role-based access control. Data governance and compliance standards. Advanced ML models for detecting row-value data anomalies. The models will adapt to the business and data requirements of users. You can add any number of data sources, records, or attributes. For unpredictable volume spikes, well-equipped. Support streaming and batch processing. Data is continuously monitored to provide real-time notification, with no impact on pipeline performance. Easy boarding, integration, investigation. Telmai is a platform that allows Data Teams to detect and investigate anomalies in real-time. No-code on-boarding. Connect to your data source, and select alerting channels. Telmai will automatically learn data and alert you if there are unexpected drifts.

Monitor your data health, and monitor your pipeline performance. Get unified visibility for all pipelines that use cloud-native tools such as Apache Spark, Snowflake and BigQuery. A platform for Data Engineers that provides observability. Data engineering is becoming more complex as business stakeholders demand it. Databand can help you catch-up. More pipelines, more complexity. Data engineers are working with more complex infrastructure and pushing for faster release speeds. It is more difficult to understand why a process failed, why it is running late, and how changes impact the quality of data outputs. Data consumers are frustrated by inconsistent results, model performance, delays in data delivery, and other issues. A lack of transparency and trust in data delivery can lead to confusion about the exact source of the data. Pipeline logs, data quality metrics, and errors are all captured and stored in separate, isolated systems.

Cloudingo makes managing customer data super simple, from deduping to importing to migrating. Salesforce is great for managing customers. Salesforce is great for managing customers. But it falls short when it comes to data quality. Data quality is a problem. There are duplicate records, customer data that doesn’t make sense, and reports that are a little...off. Do you sound familiar? You can only merge dupes one by one, native solutions, custom codes, and spreadsheets. It shouldn't be a problem to ensure the accuracy of customer data. Or spend a lot of time cleaning up and managing Salesforce. You've wasted too much time putting at risk relationships, losing opportunities, and dealing in chaos. It's time for you to change it. Imagine a tool that transforms your Salesforce data from a messy, confusing, and unreliable mess into a lead-nurturing, sales-producing machine.

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

Better data can help you connect with your customers. The industry's best data quality platform. Clean, protect, and improve your data. RingLead Cleanse employs patented duplicate merging technology that detects and eliminates duplicates within your CRM or MAP. Protect your CRM and MAP databases from dirty data at source with perimeter protection. RingLead Route gives you complete control over the lead-to rep process. It has configurable workflows as well as a powerful rules engine that routes all Salesforce objects. While assigning leads in a timely manner and accurately is a top priority, many organizations still rely upon primitive routing methods. Leads are assigned to the wrong rep, qualified leads slip through the cracks, and conversions suffer.

Digna is a solution powered by AI that addresses the challenges of data quality management in modern times. It is domain agnostic and can be used in a variety of sectors, including finance and healthcare. Digna prioritizes privacy and ensures compliance with stringent regulations. It's also built to scale and grow with your data infrastructure. Digna is flexible enough to be installed on-premises or in the cloud, and it aligns with your organization's needs and security policies. Digna is at the forefront of data quality solutions. Its user-friendly design, combined with powerful AI analytics, makes Digna an ideal solution for businesses looking to improve data quality. Digna's seamless integration, real time monitoring, and adaptability make it more than just a tool. It is a partner on your journey to impeccable data quality.

Snowplow is a data collection platform that is best in class for Data Teams. Snowplow allows you to collect rich, high-quality data from all your products and platforms. Your data is instantly available and delivered to your chosen data warehouse. This allows you to easily join other data sets to power BI tools, custom reporting, or machine learning models. The Snowplow pipeline runs in your cloud (AWS or GCP), giving your complete control over your data. Snowplow allows you to ask and answer any questions related to your business or use case using your preferred tools.

Accurity, the all in one data intelligence platform, gives you a complete understanding of your company and complete trust with your data. This will allow you to make faster business-critical decisions, increase revenue, lower costs, and ensure data compliance. You can engage and satisfy your customers with accurate, timely and relevant data. This will help you to increase brand awareness and drive sales conversions. You can access everything from one interface, automate quality checks and data quality issues workflows. This allows you to lower infrastructure and personnel costs and allow you to spend more time using your data than managing it. You can unlock the true value of your data by improving your decision-making process, identifying inefficiencies and finding valuable customer and product information to increase your company's innovation.

We are a leader for Data Quality & ML Models for enterprises adopting a modern data management ecosystem, multi-cloud and ML. Algorithms for tracking Data Anomalies in Azure GCP and AWS databases. Measure and monitor data issues across all cloud database management tools, data silos and data silos using a single centralized tool. Quality is in the eyes of the beholder. Data issues can have different implications depending where you are in the enterprise. Qualdo was the first to organize all data quality issues from the perspective of multiple enterprise stakeholders and present a unified view. Use powerful auto-resolution algorithms for tracking and isolating critical data issues. Use robust reports and alerts for managing your enterprise regulatory compliance.

The modern data workspace. All your data assets, from data tables to reports, will be instantly discoverable. The combination of powerful search algorithms and easy browsing makes it easy to find the right asset. Atlan automatically generates data quality profiles that make it easy to detect bad data. We have you covered, from automatic variable type detection and frequency distribution to missing values or outlier detection. Atlan takes the hassle out of managing and governing your data ecosystem. Atlan's bots analyze SQL query history to automatically construct data lineage. They also auto-detect PII information. This allows you to create dynamic access policies and best-in-class governance. Our Excel-like query builder allows anyone to query multiple data lakes, warehouses, and DBs. Native integrations with tools such as Tableau and Jupyter make data collaboration possible.

With exceptional functionality for data integration, quality and cleansing, maximize the value of all structured and unstructured data in your organization. SAP Data Services software increases the quality of enterprise data. It is part of SAP's Information Management Layer. It delivers timely, relevant, and trusted information to help drive better business outcomes. Transform your data into a reliable, always-available resource for business insights and use it to streamline operations and maximize efficiency. Get contextual insight and unlock the true potential of your data with a complete view of all your information. Access to any size data and any source. Standardizing and matching data can improve decision-making and operational efficiency. This will reduce duplicates, identify relationships and address quality issues proactively. Use intuitive tools to unify critical data whether it is on-premise, in the cloud or within Big Data.

Find opportunities to increase revenue, improve the effectiveness of functional teams, and provide great customer experiences. Poor CRM data is a problem that must be fixed immediately. Learn how CRM data can hinder sales and what you should do about it. Higher quality data can help you generate up to 70% more revenue. You can control the frequency of assessment, which allows you to instantly gauge the impact of a list load and current data quality practices. You can compare your data quality to the industry average by aggregating analysis of duplicate, invalid, and malformed data across CRM objects. This step-by-step guide will show you where to focus your cleanup efforts, how long each task takes, and which tools you can use to restore quality. What you don't know could be dangerous. Get your Data Trust Score, and a detailed report about the quality and health your customer data.

Data can disrupt markets and open new frontiers, but it only works when it is trusted and understood. Stakeholders in your organization can collaborate to achieve data excellence by leveraging our AI/ML-enhanced cloud-based solution, which is built with 25 years worth of best practices. With hundreds of pre-built reports and embedded best practices, you can quickly identify and remediate data quality issues. Cleanse data before or during data migration. Track data quality in real time with customizable data intelligence dashboards. Monitor data objects continuously and automatically initiate remediation workflows to direct them to the correct data owners. To accelerate future data initiatives, consolidate data on a single cloud-based platform. All data stakeholders working together in one system will reduce effort and improve results.

Crux is used by the most powerful people to increase external data integration, transformation and observability, without increasing their headcount. Our cloud-native data technology accelerates the preparation, observation, and delivery of any external dataset. We can guarantee you receive high-quality data at the right time, in the right format, and in the right location. Automated schema detection, delivery schedule inference and lifecycle management are all tools that can be used to quickly build pipelines from any external source of data. A private catalog of linked and matched data products will increase your organization's discoverability. To quickly combine data from multiple sources and accelerate analytics, enrich, validate, and transform any data set, you can enrich, validate, or transform it.

Synthesized can help you unlock the full potential of your data projects and AI. We automate all stages of data preparation and provisioning with cutting-edge AI. The platform synthesizes data without exposing personal information or causing compliance issues. Software to prepare and provide accurate synthetic data for building better models at scale. Synthesized solves the problem of data sharing for businesses. 40% of companies that invest in AI can't report business benefits. Our easy-to-use platform allows data scientists, product, and marketing teams to focus on revealing critical insight. Without representative data, testing data-driven applications can be difficult. This can lead to problems when services go live.

DQ For Dynamics is a data management solution for MS Dynamics CRM. This software is specifically designed to give you customer data that you can trust. Our software is designed to give Dynamics 365 users and CRM administrators the ability to maintain and manage CRM data quality. DQ for Dynamics is integrated into Dynamics 365. It allows you to capture, cleanse, and consolidate records in your CRM system. This will give you a single customer view, and make your data suitable for business use. Duplicate review times can be reduced up to four times compared to the standard merge review. Our multi-record review screen allows you to easily set up rules and review duplicates. Increase the effectiveness of your sales tracking, marketing campaigns, and end-to–end reporting. To allow easy segmentation of CRM data, fix the route problem.

This platform is the ultimate tool for expanding your business with data-driven decisions. Every step of your supply chain journey can be improved. Our no-code platform improves the quality and quantity of master data to provide you with a range of optimization solutions, including inventory planning and distribution network. Trusted data-driven analytics can help you prevent critical issues from occurring and make crucial real-time adjustments. You can build trust in your data and manage it with confidence. Our platform is user-friendly and provides financial institutions with data-driven insights that are transparent and easy to use to improve their financial processes. We provide eXplainableAI to business professionals so they can create advanced financial models and improve their decision-making. Rulex Academy will help you learn how to analyze your data, create workflows, understand algorithms, and optimize complex processes using our interactive online training courses.

Only Data Observability platform that allows complete control over enterprise data systems. Comprehensive, cross-sectional visibility of complex, interconnected data systems. Synthesizes signals across workloads and data quality, security, infrastructure, and security. Data processing and operational efficiency are improved. Automates data quality monitoring from start to finish for rapidly changing and mutable datasets. Acceldata offers a single window to identify, predict, and fix data problems. Complete data issues can be fixed in real-time. You can observe the flow of business data from one pane of glass. Find anomalies in interconnected data pipelines.

iCEDQ, a DataOps platform that allows monitoring and testing, is a DataOps platform. iCEDQ is an agile rules engine that automates ETL Testing, Data Migration Testing and Big Data Testing. It increases productivity and reduces project timelines for testing data warehouses and ETL projects. Identify data problems in your Data Warehouse, Big Data, and Data Migration Projects. The iCEDQ platform can transform your ETL or Data Warehouse Testing landscape. It automates it from end to end, allowing the user to focus on analyzing the issues and fixing them. The first edition of iCEDQ was designed to validate and test any volume of data with our in-memory engine. It can perform complex validation using SQL and Groovy. It is optimized for Data Warehouse Testing. It scales based upon the number of cores on a server and is 5X faster that the standard edition.

We make data for the world's most valuable companies. Innodata solves your most difficult data engineering problems using artificial intelligence and human expertise. Innodata offers the services and solutions that you need to harness digital information at scale and drive digital disruption within your industry. We secure and efficiently collect and label sensitive data. This provides ground truth that is close to 100% for AI and ML models. Our API is simple to use and ingests unstructured data, such as contracts and medical records, and generates structured XML that conforms to schemas for downstream applications and analytics. We make sure that mission-critical databases are always accurate and up-to-date.

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

ThinkData Works provides a robust catalog platform for discovering, managing, and sharing data from both internal and external sources. Enrichment solutions combine partner data with your existing datasets to produce uniquely valuable assets that can be shared across your entire organization. The ThinkData Works platform and enrichment solutions make data teams more efficient, improve project outcomes, replace multiple existing tech solutions, and provide you with a competitive advantage.

Aggua is an AI platform with augmented data fabric that gives data and business teams access to their data. It creates Trust and provides practical Data Insights for a more holistic and data-centric decision making. With just a few clicks, you can find out what's happening under the hood of your data stack. You can access data lineage, cost insights and documentation without interrupting your data engineer's day. With automated lineage, data engineers and architects can spend less time manually tracing what data type changes will break in their data pipelines, tables, and infrastructure.

Global leader in software, solutions, and business applications that manage location and geospatial information. The 9th-12th November was the first digital Smarter Data, Smarter World Conference. We are grateful to everyone who attended. If you missed a presentation, or want to see it again, you can download our on-demand webinars. The 1Integrate Google BigQuery DataStore provides Executive Leadership Data Quality Trends. We unlock the potential of location data by bringing together innovative solutions, industry knowledge, and our vast customer base. We strive to make the world safer, more sustainable, and more intelligent for the future. Data holds the key to these goals, according to us. Information and insight are now at the center of the network enterprise as we move into the age digital utility.

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.

With automated data quality profiling, and synthetic data generation, adopting data-centric AI is easier than ever. We help data scientists unlock the full potential of data. YData Fabric enables users to easily manage and understand data assets, synthetic data, for fast data access and pipelines, for iterative, scalable and iterative flows. Better data and more reliable models delivered on a large scale. Automated data profiling to simplify and speed up exploratory data analysis. Upload and connect your datasets using an easy-to-configure interface. Synthetic data can be generated that mimics real data's statistical properties and behavior. By replacing real data with synthetic data, you can enhance your datasets and improve your models' efficiency. Pipelines can be used to refine and improve processes, consume data, clean it up, transform your data and improve its quality.

Enhance monitoring, visualization, remediation, reconciliation, and reconciliation to improve the quality of your data at-rest and in-motion. Data quality should be part of your company's DNA. To get a complete view of your data's journey throughout your organization, no matter where it is located, go beyond the basic quality checks. Continuous quality monitoring and point to-point reconciliation are essential for building trust in data and providing consistent insights. Data360 DQ+ automates data quality monitoring across the entire data supply chain, starting at the point information enters your organization. This allows you to monitor data in motion. Operational data quality includes validating counts and amounts across multiple sources and tracking timeliness to meet external or internal SLAs. Also, checks to ensure totals remain within set limits are examples.

Experian Data Quality is a leader in data quality and data management solutions. Our comprehensive solutions can validate, standardize and enrich customer data. We also profile and monitor it to ensure that it is suitable for purpose. Our software can be customized to any environment and any vision with flexible SaaS or on-premise deployment models. Real-time address verification solutions allow you to keep your address data current and preserve the integrity of your contact information. Comprehensive data quality management solutions allow you to analyze, transform, and manage your data. You can even create data processing rules specific to your business. Experian Data Quality's phone validation tools can help you improve your mobile/SMS marketing efforts.

The Data Comparison Tool. It is easy to compare data from files (Excel and csv) and queries (MS-SQL and Oracle, Amazon Redshift and MySQL, and many more ...) Don't waste your time reading endless tutorials, spreadsheets, and formulas that are useless for just one instance. Instead, let the clicks do all the work and compare A with B without having to learn how to code. If you find yourself in any of these situations, you should not waste your time on things that are more important to you.

High-volume, disconnected data can be quickly transformed into actionable business insights using scalable enterprise data quality. Trillium Quality, a flexible, powerful data quality tool, supports your rapidly changing business requirements, data sources, and enterprise infrastructures, including big data and cloud. Its data cleansing features and standardization capabilities automatically understand global data such as customer, product, and financial data in any context. Pre-formatting and preprocessing are unnecessary. Trillium Quality services can be deployed on-premises or remotely in real time, in batch or in the cloud. They use the same rules and standards across a wide range of applications and systems. Open APIs allow you to seamlessly connect to third-party and custom applications while centrally managing and controlling data quality services.

The Convertr platform gives marketers visibility and control over data processes and lead quality to create higher performing demand programs. When you take control of your lead processes in the beginning, you build more scalable operations and strategic teams that can stay focused on revenue driving activities. Improve Productivity: Weeks to months of manual lead data processing can be reallocated to revenue driving activities Focus on Performance: Teams work off trusted data to make better decisions and optimize programs Drive Data Alignment: Data moves between teams and platforms in usable, analyzable formats

The BiG EVAL platform provides powerful software tools to ensure and improve data quality throughout the entire lifecycle of information. BiG EVAL's data quality and testing software tools are built on the BiG EVAL platform, a comprehensive code base that aims to provide high performance and high flexibility data validation. All features were developed through practical experience gained from working with customers. It is crucial to ensure high data quality throughout the data lifecycle. This is essential for data governance. BiG EVAL DQM, an automation solution, supports you in all aspects of data quality management. Continuous quality checks validate enterprise data, provide a quality indicator, and support you in solving quality problems. BiG EVAL DTA allows you to automate testing tasks within your data-oriented project.

Over 40 years, we have built our analytics machine and worked with countless clients. We are constantly improving our approach to the modern enterprise. This means that you can see the future and have access to all data. The goal is simple. To enable informed decision-making and help you drive business results. Accessible data is the key to a sophisticated data strategy. How you see your data, its trends and patterns, will determine how useful it is. You can empower your organization to make strategic decisions by using real-time, personalized, and self-service dashboards that bring this data to life. You don't have to rely on gut feelings, or worse, bury yourself in ambiguity. Your entire company can organize around the same information, and grow with exceptional visualization and reporting.

Waaila, a comprehensive application that monitors data quality, is supported by hundreds of analysts around the world. It helps to avoid disasters caused by poor data quality. Validate your data to take control of your analytics. They must be precise to maximize their potential, therefore validation and monitoring are essential. It is crucial that the data be accurate and reliable in order to serve its true purpose and allow for business growth. Marketing strategies that are more effective will be more efficient if they are of higher quality. You can rely on the accuracy and quality of your data to make data-driven decisions that will lead to the best results. Automated validation saves time and energy and delivers better results. Rapid attack discovery helps to prevent huge impacts and opens up new opportunities. The application management and navigation are simple, which allows for quick data validation and efficient processes that enable the issue to be quickly identified and solved.

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.

Deliver tangible strategic value, quickly. With AI-driven automation, you can ensure end-to-end support of data quality requirements across users and data types. No matter what type of initiative your organization is working on--from data migration to next-gen analytics--Informatica Data Quality has the flexibility you need to easily deploy data quality for all use cases. Facilitate collaboration between IT and business stakeholders and empower business users. All use cases and all workloads require management of the quality of multicloud and on-premises data. Integrates human tasks into the workflow. Business users can review, correct, or approve exceptions during the automated process. To uncover relationships and detect problems, profile data is used to perform iterative analysis of data. AI-driven insights can automate the most important tasks and simplify data discovery to increase productivity.

Our data quality management solutions can be relied upon whether you are preparing for a migration or looking to gain reliable customer insight. WHAT DOES DATA QUALITY-MANAGEMENT MEAN? Experian offers powerful data profiling, data discovery and data cleansing and enrichment. Process orchestration is also possible. Full-volume analyses can also be performed with Experian. It's now easier than ever to gain insight into your business data. Our solutions enable you to connect seamlessly to hundreds of data sources to eliminate duplicates, correct errors, standardize formats, and remove duplicates. You will have a better understanding of your customers and business operations if you have better data quality.