Alternatives to Mosaic AIOps

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.

ANSI SQL allows you to analyze petabytes worth of data at lightning-fast speeds with no operational overhead. Analytics at scale with 26%-34% less three-year TCO than cloud-based data warehouse alternatives. You can unleash your insights with a trusted platform that is more secure and scales with you. Multi-cloud analytics solutions that allow you to gain insights from all types of data. You can query streaming data in real-time and get the most current information about all your business processes. Machine learning is built-in and allows you to predict business outcomes quickly without having to move data. With just a few clicks, you can securely access and share the analytical insights within your organization. Easy creation of stunning dashboards and reports using popular business intelligence tools right out of the box. BigQuery's strong security, governance, and reliability controls ensure high availability and a 99.9% uptime SLA. Encrypt your data by default and with customer-managed encryption keys

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.

Qrvey is the only solution for embedded analytics with a built-in data lake. Qrvey saves engineering teams time and money with a turnkey solution connecting your data warehouse to your SaaS application. Qrvey’s full-stack solution includes the necessary components so that your engineering team can build less software in-house. Qrvey is built for SaaS companies that want to offer a better multi-tenant analytics experience. Qrvey's solution offers: - Built-in data lake powered by Elasticsearch - A unified data pipeline to ingest and analyze any type of data - The most embedded components - all JS, no iFrames - Fully personalizable to offer personalized experiences to users With Qrvey, you can build less software and deliver more value.

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.

Domo puts data to work for everyone so they can multiply their impact on the business. Underpinned by a secure data foundation, our cloud-native data experience platform makes data visible and actionable with user-friendly dashboards and apps. Domo helps companies optimize critical business processes at scale and in record time to spark bold curiosity that powers exponential business results.

Composable is an enterprise-grade DataOps platform designed for business users who want to build data-driven products and create data intelligence solutions. It can be used to design data-driven products that leverage disparate data sources, live streams, and event data, regardless of their format or structure. Composable offers a user-friendly, intuitive dataflow visual editor, built-in services that facilitate data engineering, as well as a composable architecture which allows abstraction and integration of any analytical or software approach. It is the best integrated development environment for discovering, managing, transforming, and analysing enterprise data.

It takes only days to wrap any data source with a single reference Data API and simplify access to reporting and analytics data across your teams. Make it easy for application developers and data engineers to access the data from any source in a streamlined manner. - The single schema-less Data API endpoint - Review, configure metrics and dimensions in one place via UI - Data model visualization to make faster decisions - Data Export management scheduling API Our proxy perfectly fits into your current API management ecosystem (versioning, data access, discovery) no matter if you are using Mulesoft, Apigee, Tyk, or your homegrown solution. Leverage the capabilities of Data API and enrich your products with self-service analytics for dashboards, data Exports, or custom report composer for ad-hoc metric querying. Ready-to-use Report Builder and JavaScript components for popular charting libraries (Highcharts, BizCharts, Chart.js, etc.) makes it easy to embed data-rich functionality into your products. Your product or service users will love that because everybody likes to make data-driven decisions! And you will not have to make custom report queries anymore!

Founded in 2018, Pecan is a predictive analytics platform that leverages its pioneering Predictive GenAI to remove barriers to AI adoption, making predictive modeling accessible to all data and business teams. Guided by generative AI, companies can obtain precise predictions across various business domains without the need for specialized personnel. Predictive GenAI enables rapid model definition and training, while automated processes accelerate AI implementation. With Pecan's fusion of predictive and generative AI, realizing the business impact of AI is now far faster and easier.

Fivetran is the smartest method to replicate data into your warehouse. Our zero-maintenance pipeline is the only one that allows for a quick setup. It takes months of development to create this system. Our connectors connect data from multiple databases and applications to one central location, allowing analysts to gain profound insights into their business.

We want ML engineers not to have to worry about data engineering and instead focus on what they are passionate about, building better models in a shorter time. Our product is a powerful framework which makes it 10x faster and easier for developers to explore and understand visual data at scale. Automate the creation of custom interval attributes with pre-trained extractors, or any other model. Custom attributes can be used to visualize data and analyze model performance. You can query, find rare edge cases, and curate training data across your entire data lake using custom attributes. You can easily save, modify, version, comment, and share frames, sequences, or objects with colleagues and third parties. SiaSearch is a data management platform that automatically extracts frame level, contextual metadata and uses it for data exploration, selection, and evaluation. These tasks can be automated with metadata to increase engineering productivity and eliminate the bottleneck in building industrial AI.

ClearML is an open-source MLOps platform that enables data scientists, ML engineers, and DevOps to easily create, orchestrate and automate ML processes at scale. Our frictionless and unified end-to-end MLOps Suite allows users and customers to concentrate on developing ML code and automating their workflows. ClearML is used to develop a highly reproducible process for end-to-end AI models lifecycles by more than 1,300 enterprises, from product feature discovery to model deployment and production monitoring. You can use all of our modules to create a complete ecosystem, or you can plug in your existing tools and start using them. ClearML is trusted worldwide by more than 150,000 Data Scientists, Data Engineers and ML Engineers at Fortune 500 companies, enterprises and innovative start-ups.

Molecula, an enterprise feature store, simplifies, speeds up, and controls big-data access to power machine scale analytics and AI. Continuously extracting features and reducing the data dimensionality at the source allows for millisecond queries, computations, and feature re-use across formats without copying or moving any raw data. The Molecula feature storage provides data engineers, data scientists and application developers with a single point of access to help them move from reporting and explaining with human scale data to predicting and prescribing business outcomes. Enterprises spend a lot of time preparing, aggregating and making multiple copies of their data before they can make any decisions with it. Molecula offers a new paradigm for continuous, real time data analysis that can be used for all mission-critical applications.

Simplified IT/OT Integration, Data Engineering & Real-Time Edge Intelligence. Easy to use, cross platform, open architecture edge computing for industrial time series data. Foghub provides the Critical-Path for IT/OT convergence. It connects Operations (Sensors and Devices, and Systems) and Business (People, Processes and Applications). This allows automated data acquisition, transformations, advanced analytics, and ML. You can manage large volumes, velocity, and variety of industrial data with the out-of-the box support for all data types, most industrial network protocols, OT/lab system, and databases. Automate data collection about your production runs, batches and parts, as well as process parameters, asset condition, performance, utility costs, consumables, operators and their performance. Foghub is designed for scale and offers a wide range of capabilities to handle large volumes of data at high velocity.

Data engineers and scientists can be 95% better at their jobs with ready access to the most flexible semantic layer, explainable AI and reusable data modelling. They can create and expand semantic models, understand data interrelationships, and run federated query to speed up time to insight. Stardog's graph data virtualization and high performance graph database are the best available -- at a price that is up to 57x less than competitors -- to connect any data source, warehouse, or enterprise data lakehouse without copying or moving data. Scale users and use cases at a lower infrastructure cost. Stardog's intelligent inference engine applies expert knowledge dynamically at query times to uncover hidden patterns and unexpected insights in relationships that lead to better data-informed business decisions and outcomes.

Vaex.io aims to democratize the use of big data by making it available to everyone, on any device, at any scale. Your prototype is the solution to reducing development time by 80%. Create automatic pipelines for every model. Empower your data scientists. Turn any laptop into an enormous data processing powerhouse. No clusters or engineers required. We offer reliable and fast data-driven solutions. Our state-of-the art technology allows us to build and deploy machine-learning models faster than anyone else on the market. Transform your data scientists into big data engineers. We offer comprehensive training for your employees to enable you to fully utilize our technology. Memory mapping, a sophisticated Expression System, and fast Out-of-Core algorithms are combined. Visualize and explore large datasets and build machine-learning models on a single computer.

DatErica: Revolutionizing Data Processing DatErica, a cutting edge data processing platform, automates and streamlines data operations. It provides scalable, flexible solutions to complex data requirements by leveraging a robust technology stack that includes Node.js. The platform provides advanced ETL capabilities and seamless data integration across multiple sources. It also offers secure data warehousing. DatErica’s AI-powered tools allow sophisticated data transformation and verification, ensuring accuracy. Users can make informed decisions with real-time analytics and customizable dashboards. The user-friendly interface simplifies the workflow management while real-time monitoring, alerts and notifications enhance operational efficiency. DatErica is perfect for data engineers, IT teams and businesses that want to optimize their data processes.

Kestra is a free, open-source orchestrator based on events that simplifies data operations while improving collaboration between engineers and users. Kestra brings Infrastructure as Code to data pipelines. This allows you to build reliable workflows with confidence. The declarative YAML interface allows anyone who wants to benefit from analytics to participate in the creation of the data pipeline. The UI automatically updates the YAML definition whenever you make changes to a work flow via the UI or an API call. The orchestration logic can be defined in code declaratively, even if certain workflow components are modified.

Presto is an open-source distributed SQL query engine that allows interactive analytic queries against any data source, from gigabytes up to petabytes.

Nexla's automated approach to data engineering has made it possible for data users for the first time to access ready-to-use data without the need for any connectors or code. Nexla is unique in that it combines no-code and low-code with a developer SDK, bringing together users of all skill levels on one platform. Nexla's data-as a-product core combines integration preparation, monitoring, delivery, and monitoring of data into one system, regardless of data velocity or format. Nexla powers mission-critical data for JPMorgan and Doordash, LinkedIn LiveRamp, J&J, as well as other leading companies across industries.

Peliqan.io provides a data platform that is all-in-one for business teams, IT service providers, startups and scale-ups. No data engineer required. Connect to databases, data warehouses, and SaaS applications. In a spreadsheet interface, you can explore and combine data. Business users can combine multiple data sources, clean data, edit personal copies, and apply transformations. Power users can use SQL on anything, and developers can use Low-code to create interactive data apps, implement writing backs and apply machine intelligence.

Ascend provides data teams with a unified platform that allows them to ingest and transform their data and create and manage their analytics engineering and data engineering workloads. Ascend is supported by DataAware intelligence. Ascend works in the background to ensure data integrity and optimize data workloads, which can reduce maintenance time by up to 90%. Ascend's multilingual flex-code interface allows you to use SQL, Java, Scala, and Python interchangeably. Quickly view data lineage and data profiles, job logs, system health, system health, and other important workload metrics at a glance. Ascend provides native connections to a growing number of data sources using our Flex-Code data connectors.

AtScale accelerates and simplifies business intelligence. This results in better business decisions and a faster time to insight. Reduce repetitive data engineering tasks such as maintaining, curating, and delivering data for analysis. To ensure consistent KPI reporting across BI tools, you can define business definitions in one place. You can speed up the time it takes to gain insight from data and also manage cloud compute costs efficiently. No matter where your data is located, you can leverage existing data security policies to perform data analytics. AtScale's Insights models and workbooks allow you to perform Cloud OLAP multidimensional analysis using data sets from multiple providers - without any data prep or engineering. To help you quickly gain insights that you can use to make business decisions, we provide easy-to-use dimensions and measures.

AnalyticsCreator lets you extend and adjust an existing DWH. It is easy to build a solid foundation. The reverse engineering method of AnalyticsCreator allows you to integrate code from an existing DWH app into AC. So, more layers/areas are included in the automation. This will support the change process more extensively. The extension of an manually developed DWH with an ETL/ELT can quickly consume resources and time. Our experience and studies found on the internet have shown that the longer the lifecycle the higher the cost. You can use AnalyticsCreator to design your data model and generate a multitier data warehouse for your Power BI analytical application. The business logic is mapped at one place in AnalyticsCreator.

Advana, a new-generation data engineering and data-science software, is designed to make implementing and scaling up data analytics easier and faster. This gives you the freedom to focus your attention on what's most important to you: solving your business challenges. Advana offers a variety of data analytics features and capabilities that will allow you to manage, analyze, and transform your data in an efficient and effective manner. Modernize your legacy data analytics solutions. Deliver business value quicker and cheaper by leveraging the no code paradigm. Retain domain experts while computing technology evolves. Collaboration across business functions and IT is seamless with a common interface. You can develop solutions for new technologies without learning new coding. As new technologies become available, you can easily port your solutions.

Advanced Analytics Software Platform that Helps Sales, Marketing and Technology Leaders Make Great Business Decisions Based On Powerful Data-Driven Information. This software addresses the wide range of AI requirements across data infrastructure, data engineering, and data analytics. Each client's unique requirements are met with customized UI, workflows, and proprietary algorithms. Modular components allow for custom configurations. This component supports, augments, and automates decision-making. Better business results are possible by eliminating human biases. The adoption rate of AI is unprecedented. Leading companies need a rapid and scaleable implementation strategy to stay competitive. These four capabilities can be combined to create a scalable business impact.

AI teams are faced with challenges that require new technologies. These technologies are built by us. Existing data lakes and data warehouses do not work with unstructured data like text, images, or videos. AI and software development go hand in hand. Built with data scientists, ML experts, and data engineers at heart. Don't reinvent your wheel! Production is fast and cost-effective. All your data is stored by you. Your machines are used to train your models. Existing data lakes and data warehouses do not work with unstructured data like text, images, or videos. New technologies are required for AI teams. These technologies are built by us. Studio is an extension to BitBucket, GitLab, and GitHub. Register for the online SaaS version, or contact us to start an on-premise installation

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.

Your offline data can be used to make real-time predictions, without the need for custom pipelines. Data consistency is achieved between offline training and online prediction, eliminating train-serve bias. Standardize data engineering workflows within a consistent framework. Feast is used by teams to build their internal ML platforms. Feast doesn't require dedicated infrastructure to be deployed and managed. Feast reuses existing infrastructure and creates new resources as needed. You don't want a managed solution, and you are happy to manage your own implementation. Feast is supported by engineers who can help with its implementation and management. You are looking to build pipelines that convert raw data into features and integrate with another system. You have specific requirements and want to use an open-source solution.

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.

Connecting every data source with analytics services on a single AI-powered platform will transform how people access, manage, and act on data and insights. All your data. All your teams. All your teams in one place. Create an open, lake-centric hub to help data engineers connect data from various sources and curate it. This will eliminate sprawl and create custom views for all. Accelerate analysis through the development of AI models without moving data. This reduces the time needed by data scientists to deliver value. Microsoft Teams, Microsoft Excel, and Microsoft Teams are all great tools to help your team innovate faster. Connect people and data responsibly with an open, scalable solution. This solution gives data stewards more control, thanks to its built-in security, compliance, and governance.

Archon Data Store™ is an open-source archive lakehouse platform that allows you to store, manage and gain insights from large volumes of data. Its minimal footprint and compliance features enable large-scale processing and analysis of structured and unstructured data within your organization. Archon Data Store combines data warehouses, data lakes and other features into a single platform. This unified approach eliminates silos of data, streamlining workflows in data engineering, analytics and data science. Archon Data Store ensures data integrity through metadata centralization, optimized storage, and distributed computing. Its common approach to managing data, securing it, and governing it helps you innovate faster and operate more efficiently. Archon Data Store is a single platform that archives and analyzes all of your organization's data, while providing operational efficiencies.

Sentrana allows you to create AI and data engineering pipes wherever your data is. You can also share your AI, Data and Pipelines with anyone, anywhere. Sentrana gives you the ability to move seamlessly between different compute environments. All your data and work are automatically replicated to wherever you need them. Sentrana offers a wide range of building blocks that you can use to create custom AI and Data Engineering pipes. You can quickly assemble and test multiple pipelines to create the AI that you need. Your data can be transformed into AI with almost zero effort and minimal cost. Sentrana is an open platform that allows you to access the latest cutting-edge AI building blocks. Sentrana transforms the AI models and Pipelines you create into re-executable building blocks that can be used by anyone on your team to build their own pipelines.

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

Data analysts can now gain insights faster and without any barriers. Intelligent data stack automation, gain insights from your data 10x quicker with AI. Intelligence for the modern data-stack has arrived, a technology that was developed at Stanford's AI lab and is now available to enterprises. Use natural language to extract value from your messy data, complex and siloed in minutes. Tell your data what you want and it will generate code to execute. Automate complex data tasks in a way that is specific to your company and not covered by templated solutions. Automate data-intensive workflows using the modern data stack. Discover insights in minutes and not months. Uniquely designed and tuned to your organization's requirements. Snowflake, Databricks Redshift, BigQuery and more are integrated with dbt.

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.

Dataplane's goal is to make it faster and easier to create a data mesh. It has robust data pipelines and automated workflows that can be used by businesses and teams of any size. Dataplane is more user-friendly and places a greater emphasis on performance, security, resilience, and scaling.

Delta Lake is an open-source storage platform that allows ACID transactions to Apache Spark™, and other big data workloads. Data lakes often have multiple data pipelines that read and write data simultaneously. This makes it difficult for data engineers to ensure data integrity due to the absence of transactions. Your data lakes will benefit from ACID transactions with Delta Lake. It offers serializability, which is the highest level of isolation. Learn more at Diving into Delta Lake - Unpacking the Transaction log. Even metadata can be considered "big data" in big data. Delta Lake treats metadata the same as data and uses Spark's distributed processing power for all its metadata. Delta Lake is able to handle large tables with billions upon billions of files and partitions at a petabyte scale. Delta Lake allows developers to access snapshots of data, allowing them to revert to earlier versions for audits, rollbacks, or to reproduce experiments.

Lumenore Business Intelligence with no-code analytics. Get actionable intelligence that’s connected to your data - wherever it’s coming from. Next-generation business intelligence and analytics platform. We embrace change every day and strive to push the boundaries of technology and innovation to do more, do things differently, and, most importantly, to provide people and companies with the right insight in the most efficient way. In just a few clicks, transform huge amounts of raw data into actionable information. This program was designed with the user in mind.

Switchboard, a data engineering automation platform that is driven by business teams, allows you to aggregate disparate data at scale and make better business decisions. Get timely insights and precise forecasts. No more outdated manual reports or poorly designed pivot tables that don’t scale. Directly pull data from the right formats and reconfigure them in a non-code environment. Reduce dependency on engineering teams. API outages, bad schemas and missing data are gone thanks to automatic monitoring and backfilling. It's not a dumb API. Instead, it's an ecosystem of pre-built connectors which can be quickly and easily adapted to transform raw data into strategic assets. Our team of experts have worked in data teams at Google, Facebook, and other companies. These best practices have been automated to improve your data game. Data engineering automation platform that enables authoring and workflow processes. It is designed to scale with terabytes.

Learn how CloudWorx Intergraph Smart 3D connects with the point cloud and allows users to create hybrids between existing plants and newly modeled parts. Intergraph Smart®, Laser Data Engineer offers state-of-the art point cloud rendering performance in CloudWorx. Intergraph Smart Smart 3D users can access the JetStream point cloud platform. Smart Laser Data Engineer provides the ultimate in user satisfaction with its instant loading and persistent full rendering, regardless of how large the dataset is. JetStream's central data storage and administrative architecture provides high-performance point clouds to users. It also offers an easy-to use project environment that makes data distribution, user access control and backups simple and efficient, which saves time and money.

AI-powered Informatica Data Engineering streaming allows data engineers to ingest and process real-time streaming data in order to gain actionable insights.

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.

The largest global team of Fast Data and Functional Programming engineers focused on developing high-performance, customized solutions. Through rapid prototyping and proof-of-concept, we move from "thought to thing". CI/CD can help you create an ecosystem that will deliver at scale. To develop a shared vision, it is important to understand the stakeholder needs and the strategic intent. MVP should be deployed to launch the product in a most efficient and expedient manner. Continuous improvements and enhancements are made to meet new requirements. Without the ability to use the most recent tools and technology, it would be impossible to build great products or provide unmatched engineering services. We help you capitalize on opportunities, respond effectively to competitive threats, scale successful investments, and reduce organizational friction in your company's processes, structures, and culture. Knoldus assists clients in identifying and capturing the highest value and meaningful insights from their data.

K2View believes that every enterprise should be able to leverage its data to become as disruptive and agile as possible. We enable this through our Data Product Platform, which creates and manages a trusted dataset for every business entity – on demand, in real time. The dataset is always in sync with its sources, adapts to changes on the fly, and is instantly accessible to any authorized data consumer. We fuel operational use cases, including customer 360, data masking, test data management, data migration, and legacy application modernization – to deliver business outcomes at half the time and cost of other alternatives.

DataLakeHouse.io Data Sync allows users to replicate and synchronize data from operational systems (on-premises and cloud-based SaaS), into destinations of their choice, primarily Cloud Data Warehouses. DLH.io is a tool for marketing teams, but also for any data team in any size organization. It enables business cases to build single source of truth data repositories such as dimensional warehouses, data vaults 2.0, and machine learning workloads. Use cases include technical and functional examples, including: ELT and ETL, Data Warehouses, Pipelines, Analytics, AI & Machine Learning and Data, Marketing and Sales, Retail and FinTech, Restaurants, Manufacturing, Public Sector and more. DataLakeHouse.io has a mission: to orchestrate the data of every organization, especially those who wish to become data-driven or continue their data-driven strategy journey. DataLakeHouse.io, aka DLH.io, allows hundreds of companies manage their cloud data warehousing solutions.

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.

The machine learning platform that unifies data and orchestrates intelligent behavior among revenue-generating teams. It also delivers out-of the-box attribution and actionable analytics. QFlow.ai processes the gigabytes worth of data that Salesforce.com's activity table stores. To help you win more deals and generate more opportunities, we normalize, trend, or analyze your sales efforts. QFlow.ai uses data engineering for outbound activity reporting. It focuses on one crucial factor: whether they were productive. It also automatically displays critical metrics such as average days between first activity and opp creation, and average days between opp création to close. To understand trends in sales activity and productivity over time, Sales Effort data can either be filtered by a team or an individual.

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.

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.