Alternatives to DataBuck

Looker reinvents the way business intelligence (BI) works by delivering an entirely new kind of data discovery solution that modernizes BI in three important ways. A simplified web-based stack leverages our 100% in-database architecture, so customers can operate on big data and find the last mile of value in the new era of fast analytic databases. An agile development environment enables today’s data rockstars to model the data and create end-user experiences that make sense for each specific business, transforming data on the way out, rather than on the way in. At the same time, a self-service data-discovery experience works the way the web works, empowering business users to drill into and explore very large datasets without ever leaving the browser. As a result, Looker customers enjoy the power of traditional BI at the speed of the web.

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.

Manta is a unified data lineage platform that serves as the central hub of all enterprise data flows. Manta can construct lineage from report definitions, custom SQL code, and ETL workflows. Lineage is analyzed based on actual code, and both direct and indirect flows can be visualized on the map. Data paths between files, report fields, database tables, and individual columns are displayed to users in an intuitive user interface, enabling teams to understand data flows in context.

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

Datuum is an AI-powered data integration tool that offers a unique solution for organizations looking to streamline their data integration process. With our pre-trained AI engine, Datuum simplifies customer data onboarding by allowing for automated integration from various sources without coding. This reduces data preparation time and helps establish resilient connectors, ultimately freeing up time for organizations to focus on generating insights and improving the customer experience. At Datuum, we have over 40 years of experience in data management and operations, and we've incorporated our expertise into the core of our product. Our platform is designed to address the critical challenges faced by data engineers and managers while being accessible and user-friendly for non-technical specialists. By reducing up to 80% of the time typically spent on data-related tasks, Datuum can help organizations optimize their data management processes and achieve more efficient outcomes.

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.

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.

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.

Drag-and-drop rules studio allows you to profile, clean, match, and deduplicate data. Lo-code UI is a user interface that requires no programming skills. This puts power in the hands subject matter experts. You can add AI and machine learning to your existing data management process to reduce manual effort, increase accuracy, and provide full transparency on machine-led decisions. Our self-service solutions offer award-winning data quality, matching capabilities across multiple industries and are quickly configured with specialist assistance from Datactics data engineers. Datactics makes it easy to measure data against industry and regulatory standards, fix breaches in bulk, and push into reporting tools. Chief Risk Officers have full visibility and audit trails. Datactics can be used to augment data matching with Legal Entity Masters to manage client lifecycle management.

With your own data shop, create new revenue streams from the data you already have. Narrative focuses on the fundamental principles that make buying or selling data simpler, safer, and more strategic. You must ensure that the data you have access to meets your standards. It is important to know who and how the data was collected. Access new supply and demand easily for a more agile, accessible data strategy. You can control your entire data strategy with full end-to-end access to all inputs and outputs. Our platform automates the most labor-intensive and time-consuming aspects of data acquisition so that you can access new data sources in days instead of months. You'll only ever have to pay for what you need with filters, budget controls and automatic deduplication.

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.

Validate and verify your address information by comparing them with official Postal Authority databases. You can increase delivery rates, reduce returned mail, and receive postal discounts. Connect address datasources with our enterprise-class cleansing transforms. Once you have connected your address datasources, you will be able to validate and verify it. You can increase delivery rates, reduce returned mail, and get postal discounts. Identify the data elements in your address data and separate them into their parts. Correct common spelling errors and format your address data to conform with industry standards. This will improve mail delivery. Verify that an address exists against the USPS address database. You can verify whether the address is residential, business, or if it is deliveryable by USPS Delivery Point Validation. Merge validated data from multiple sources to create customized output files for your organization's workflow.

Secuvy, a next-generation cloud platform, automates data security, privacy compliance, and governance via AI-driven workflows. Unstructured data is treated with the best data intelligence. Secuvy, a next-generation cloud platform that automates data security, privacy compliance, and governance via AI-driven workflows is called Secuvy. Unstructured data is treated with the best data intelligence. Automated data discovery, customizable subjects access requests, user validations and data maps & workflows to comply with privacy regulations such as the ccpa or gdpr. Data intelligence is used to locate sensitive and private information in multiple data stores, both in motion and at rest. Our mission is to assist organizations in protecting their brand, automating processes, and improving customer trust in a world that is rapidly changing. We want to reduce human effort, costs and errors in handling sensitive data.

Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.

In a developer-friendly visual editor, you can design, debug, run, and troubleshoot data jobflows and data transformations. You can orchestrate data tasks that require a specific sequence and organize multiple systems using the transparency of visual workflows. Easy deployment of data workloads into an enterprise runtime environment. Cloud or on-premise. Data can be made available to applications, people, and storage through a single platform. You can manage all your data workloads and related processes from one platform. No task is too difficult. CloverDX was built on years of experience in large enterprise projects. Open architecture that is user-friendly and flexible allows you to package and hide complexity for developers. You can manage the entire lifecycle for a data pipeline, from design, deployment, evolution, and testing. Our in-house customer success teams will help you get things done quickly.

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.

Mozart Data is the all-in-one modern data platform for consolidating, organizing, and analyzing your data. Set up a modern data stack in an hour, without any engineering. Start getting more out of your data and making data-driven decisions today.

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.

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.

Geocoding and address quality software. Validate, deduplicate, and maintain accurate and deliverable address information. Data quality is the ability to verify the accuracy and completeness of certain data. Data quality and postal address verification involves integrating data into any address database to ensure it is reliable and serves its intended purpose. There are many sectors and operations that rely on postal addresses, such as shipping and data entry, such as geomarketing and statistics, such as transportation. Operations tuning is key to ensuring significant logistics and economic savings for enterprises. This add-value is important to make work easier, more efficient. Egon is an online data quality system that can be accessed via the internet.

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.

Datameer is your go-to data tool for exploring, preparing, visualizing, and cataloging Snowflake insights. From exploring raw datasets to driving business decisions – an all-in-one tool.

Castor is a data catalogue that can be adopted by all employees. Get a complete overview of your data environment. Our powerful search engine makes it easy to find data quickly. Access data quickly and easily by joining a new data infrastructure. Expand beyond the traditional data catalog. Modern data teams have multiple data sources. Instead of building one truth, they build it. Castor's delightful and automated documentation makes it easy to trust data. In minutes, you can get a column-level view of your cross-system data lineage. To build trust in your data, get a bird's-eye view of your data pipelines. All you need to troubleshoot data issues, conduct impact analyses, and comply with GDPR is one tool. Optimize performance, cost compliance, security, and security for data. Our automated infrastructure monitoring system will keep your data stack healthy.

Deepnote is building the best data science notebook for teams. Connect your data, explore and analyze it within the notebook with real-time collaboration and versioning. Share links to your projects with other analysts and data scientists on your team, or present your polished, published notebooks to end users and stakeholders. All of this is done through a powerful, browser-based UI that runs in the cloud.

NaturalText A.I. Your data can be used to get more. Discover relationships, build collections, and uncover hidden insights in documents and text-based data. NaturalText A.I. NaturalText A.I. uses artificial intelligence technology to uncover hidden data relationships. The software uses a variety of state-of-the art methods to understand context and analyze patterns to reveal insights - all in a human-readable manner. Discover hidden insights in your data It can be difficult, if not impossible, to find everything in your text data. Traditional search can only find information about a document. NaturalText A.I. on the other hand, uncovers new data within millions of documents, including patents and scientific papers. NaturalText A.I. NaturalText A.I. can help you uncover insights in your data that you are not currently seeing.

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.

Astronomer is the driving force behind Apache Airflow, the de facto standard for expressing data flows as code. Airflow is downloaded more than 4 million times each month and is used by hundreds of thousands of teams around the world. For data teams looking to increase the availability of trusted data, Astronomer provides Astro, the modern data orchestration platform, powered by Airflow. Astro enables data engineers, data scientists, and data analysts to build, run, and observe pipelines-as-code. Founded in 2018, Astronomer is a global remote-first company with hubs in Cincinnati, New York, San Francisco, and San Jose. Customers in more than 35 countries trust Astronomer as their partner for data orchestration.

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.

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.

Talend Data Fabric's cloud services are able to efficiently solve all your integration and integrity problems -- on-premises or in cloud, from any source, at any endpoint. Trusted data delivered at the right time for every user. With an intuitive interface and minimal coding, you can easily and quickly integrate data, files, applications, events, and APIs from any source to any location. Integrate quality into data management to ensure compliance with all regulations. This is possible through a collaborative, pervasive, and cohesive approach towards data governance. High quality, reliable data is essential to make informed decisions. It must be derived from real-time and batch processing, and enhanced with market-leading data enrichment and cleaning tools. Make your data more valuable by making it accessible internally and externally. Building APIs is easy with the extensive self-service capabilities. This will improve customer engagement.

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.

Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.

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.

Cloud-native data integration with IBM Cloud Pak data enables you to accelerate AI innovation AI-powered data integration from anywhere. Your AI and analytics can only be as good as the data they are powered by. IBM®, DataStage®, for IBM Cloud Pak®, for Data provides high-quality data through a container-based architecture. It combines industry-leading data integration, DataOps, governance, and analytics on one data and AI platform. Automation speeds up administrative tasks, helping to reduce TCO. AI-based design accelerators, out-of-the box integration with DataOps or data science services accelerate AI innovation. Multicloud integration and parallelism allow you to deliver trusted data across hybrid and multicloud environments. The IBM Cloud Pak for Data platform allows you to manage the data and analytics lifecycle. Data science, event messaging, and data warehousing are some of the services offered. Automated load balancing and parallel engine.

Unlike most data management systems, PHEMI Health DataLab is built with Privacy-by-Design principles, not as an add-on. This means privacy and data governance are built-in from the ground up, providing you with distinct advantages: Lets analysts work with data without breaching privacy guidelines Includes a comprehensive, extensible library of de-identification algorithms to hide, mask, truncate, group, and anonymize data. Creates dataset-specific or system-wide pseudonyms enabling linking and sharing of data without risking data leakage. Collects audit logs concerning not only what changes were made to the PHEMI system, but also data access patterns. Automatically generates human and machine-readable de- identification reports to meet your enterprise governance risk and compliance guidelines. Rather than a policy per data access point, PHEMI gives you the advantage of one central policy for all access patterns, whether Spark, ODBC, REST, export, and more

DataMatch Enterprise™, a highly visual data cleansing tool, is specifically designed to address customer and contact data quality problems. The platform uses a variety of proprietary and standard algorithms to identify phonetic and domain-specific variations. You can create scalable configurations that allow for deduplication, record linkage, suppression enhancement, extraction, standardization, standardization, and standardization of customer and business data. This will maximize the impact of your data throughout the enterprise.

To have complete control over your data, harness the power of data discovery, data lineage and a data catalogue. It can quickly navigate through complex data landscapes. Access the most comprehensive automated data lineage and discovery system. This gives you unprecedented visibility and trust in the most complex data environments. Octopai extracts metadata from all data environments. Octopai can instantly analyze metadata in a fast, secure, and easy process. Octopai gives you access to data lineage, data discovery, and a data catalogue, all from one central platform. In seconds, trace any data from end to end through your entire data landscape. Find the data you need automatically from any place in your data landscape. A self-creating, self updating data catalog will help you create consistency across your company.

Data Ladder is a data cleansing and quality company that helps you "get the best out of your data." We offer data matching, profiling and deduplication as well as enrichment. Our product offerings are simple and easy to understand. This allows us to provide excellent customer service and a great solution for our customers. Our products are used by Fortune 500 companies. We are proud of our reputation for listening to our customers, and constantly improving our products. Our powerful, user-friendly software allows business users from all industries to manage their data more efficiently and improve their bottom line. DataMatch Enterprise, our data quality software suite, found approximately 12%-300% more matches than the leading software companies IBM or SAS in 15 different studies. We have over 10 years of experience in R&D and counting. We are constantly improving our data-quality software solutions. This dedication has resulted in more than 4000 installations around the world.

OpenRefine (previously Google Refine), is a powerful tool to work with messy data. It can clean it, transform it into another format, and extend it with web services or external data. OpenRefine keeps your data secure on your computer until you share it or collaborate with others. Unless you wish it to, your private data will never leave your computer. It works by installing a small server on your computer. You then use your web browser for interaction with it. OpenRefine allows you to explore large data sets easily. Watch the video below to learn more about this functionality. OpenRefine can link and extend your data with many webservices. OpenRefine can also upload your cleaned data to Wikidata.

What if your data had a recommendation engine? Automated data inventory was created. A searchable catalog showed user behavior. Smart recommendations were made inline by the system as you typed queries. Alation, the first enterprise-wide collaborative data catalog, makes all this possible. It's a powerful tool that dramatically increases the productivity of analysts and the accuracy of analytics. It also empowers business decision-making for everyone. Alation provides proactive recommendations to data users through applications. Google inspired us to create a simple interface that connects the language of your business with the technical schema of your data. No more is it difficult to find the data you need due to complicated semantic translations. Are you unfamiliar with the data environment and unsure which data to use in your query. Alation allows you to build your query and provides inline recommendations that indicate whether data is trustworthy.

The open-source ML observability Platform. From validation to production, evaluate, test, and track ML models. From tabular data up to NLP and LLM. Built for data scientists and ML Engineers. All you need to run ML systems reliably in production. Start with simple ad-hoc checks. Scale up to the full monitoring platform. All in one tool with consistent APIs and metrics. Useful, beautiful and shareable. Explore and debug a comprehensive view on data and ML models. Start in a matter of seconds. Test before shipping, validate in production, and run checks with every model update. By generating test conditions based on a reference dataset, you can skip the manual setup. Monitor all aspects of your data, models and test results. Proactively identify and resolve production model problems, ensure optimal performance and continually improve it.

Upsolver makes it easy to create a governed data lake, manage, integrate, and prepare streaming data for analysis. Only use auto-generated schema on-read SQL to create pipelines. A visual IDE that makes it easy to build pipelines. Add Upserts to data lake tables. Mix streaming and large-scale batch data. Automated schema evolution and reprocessing of previous state. Automated orchestration of pipelines (no Dags). Fully-managed execution at scale Strong consistency guarantee over object storage Nearly zero maintenance overhead for analytics-ready information. Integral hygiene for data lake tables, including columnar formats, partitioning and compaction, as well as vacuuming. Low cost, 100,000 events per second (billions every day) Continuous lock-free compaction to eliminate the "small file" problem. Parquet-based tables are ideal for quick queries.

Etleap was created on AWS to support Redshift, snowflake and S3/Glue data warehouses and data lakes. Their solution simplifies and automates ETL through fully-managed ETL as-a-service. Etleap's data wrangler allows users to control how data is transformed for analysis without having to write any code. Etleap monitors and maintains data pipes for availability and completeness. This eliminates the need for constant maintenance and centralizes data sourced from 50+ sources and silos into your database warehouse or data lake.

Cognos Analytics with Watson brings BI to a new level with AI capabilities that provide a complete, trustworthy, and complete picture of your company. They can forecast the future, predict outcomes, and explain why they might happen. Built-in AI can be used to speed up and improve the blending of data or find the best tables for your model. AI can help you uncover hidden trends and drivers and provide insights in real-time. You can create powerful visualizations and tell the story of your data. You can also share insights via email or Slack. Combine advanced analytics with data science to unlock new opportunities. Self-service analytics that is governed and secures data from misuse adapts to your needs. You can deploy it wherever you need it - on premises, on the cloud, on IBM Cloud Pak®, for Data or as a hybrid option.

For AI and cloud analytics, you can ingest, prepare, or process data pipelines at large scale. Informatica's extensive data engineering portfolio includes everything you need to process big data engineering workloads for AI and analytics. This includes robust data integration, streamlining, masking, data preparation, and data quality.

The fastest way to prepare data and build data pipelines in cloud. Trifacta offers visual and intelligent guidance to speed up data preparation to help you get to your insights faster. Poor data quality can cause problems in any analytics project. Trifacta helps you to understand your data and can help you quickly and accurately clean up it. All the power without any code. Trifacta offers visual and intelligent guidance to help you get to the right insights faster. Manual, repetitive data preparation processes don't scale. Trifacta makes it easy to build, deploy, and manage self-service data networks in minutes instead of months.

Y42 is the first fully managed Modern DataOps Cloud for production-ready data pipelines on top of Google BigQuery and Snowflake.

Kylo is an enterprise-ready open-source data lake management platform platform for self-service data ingestion and data preparation. It integrates metadata management, governance, security, and best practices based on Think Big's 150+ big-data implementation projects. Self-service data ingest that includes data validation, data cleansing, and automatic profiling. Visual sql and an interactive transformation through a simple user interface allow you to manage data. Search and explore data and metadata. View lineage and profile statistics. Monitor the health of feeds, services, and data lakes. Track SLAs and troubleshoot performance. To enable user self-service, create batch or streaming pipeline templates in Apache NiFi. While organizations can spend a lot of engineering effort to move data into Hadoop, they often struggle with data governance and data quality. Kylo simplifies data ingest and shifts it to data owners via a simple, guided UI.

Montara enables BI Teams and Data Analysts to model and transform data using SQL alone, easily and seamlessly, and enjoy benefits such a modular code, CI/CD and versioning, automated testing and documentation. With Montara, analysts are able to quickly understand the impact of changes in models on analysis, reports, and dashboards. Report-level lineage is supported, as well as support for 3rd-party visualization tools like Tableau and Looker. BI teams can also perform ad hoc analysis, create dashboards and reports directly on Montara.

SAP Information Steward software allows for data profiling, monitoring, and information policy management. It is the information governance layer of SAP Business Technology Platform and can help you to anticipate risk and achieve better business outcomes. To gain continuous insight into your enterprise's data model integrity, combine data profiling, metadata management, and data lineage. You will gain a better understanding about the data quality in your data management landscape while accessing and analysing metrics using intuitive dashboards and scorecards. Supporting analysts, data stewards, IT experts, and other professionals with consistent validation rules, guidelines, can improve enterprise information management initiatives. Data profiling and metadata management are two solutions that can help you discover, assess, define and monitor the quality of your enterprise's data assets. Run what-if analyses to forecast the savings that improved data quality could bring.