Alternatives to Cazena

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

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.

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.

Qubole is an open, secure, and simple Data Lake Platform that enables machine learning, streaming, or ad-hoc analysis. Our platform offers end-to-end services to reduce the time and effort needed to run Data pipelines and Streaming Analytics workloads on any cloud. Qubole is the only platform that offers more flexibility and openness for data workloads, while also lowering cloud data lake costs up to 50%. Qubole provides faster access to trusted, secure and reliable datasets of structured and unstructured data. This is useful for Machine Learning and Analytics. Users can efficiently perform ETL, analytics, or AI/ML workloads in an end-to-end fashion using best-of-breed engines, multiple formats and libraries, as well as languages that are adapted to data volume and variety, SLAs, and organizational policies.

Business Process Management Software (BPMS & BPM Workflow Automation Software). Companies require support for workflow, forms, compliance, as well as automation routing. Low-code options make it easy to create and edit workflows. Our best-in class forms capabilities make it easy to quickly build forms, logic, and workflows for forms driven workflow processes. Many systems are already in place and need to be integrated. Our business process integrations between systems are loosely-coupled and intelligently integrated. FlowWright allows you to access standard metrics as well as those you create when automating your business. BPM analytics are an integral part of any BPM workflow management solution. FlowWright is available as a cloud solution, or in an on-premise or.NET hosted environment, including AWS and Azure. It was developed in.NET Foundation C# code. All tools are browser-based and do not require plug-ins.

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.

All your data, analytics, and AI in one unified platform. Databricks is powered by Delta Lake. It combines the best data warehouses with data lakes to create a lakehouse architecture that allows you to collaborate on all your data, analytics, and AI workloads. We are the original developers of Apache Spark™, Delta Lake, and MLflow. We believe open source software is the key to the future of data and AI. Your business can be built on an open, cloud-agnostic platform. Databricks supports customers all over the world on AWS, Microsoft Azure, or Alibaba cloud. Our platform integrates tightly with the cloud providers' security, compute storage, analytics and AI services to help you unify your data and AI workloads.

Lentiq is a data lake that allows small teams to do big tasks. You can quickly run machine learning, data science, and data analysis at scale in any cloud. Lentiq allows your teams to ingest data instantly and then clean, process, and share it. Lentiq allows you to create, train, and share models within your organization. Lentiq allows data teams to collaborate and invent with no restrictions. Data lakes are storage and process environments that provide ML, ETL and schema-on-read querying capabilities. Are you working on data science magic? A data lake is a must. The big, centralized data lake of the Post-Hadoop era is gone. Lentiq uses data pools, which are interconnected, multi-cloud mini-data lakes. They all work together to provide a stable, secure, and fast data science environment.

Dataleyk is a secure, fully-managed cloud platform for SMBs. Our mission is to make Big Data analytics accessible and easy for everyone. Dataleyk is the missing piece to achieving your data-driven goals. Our platform makes it easy to create a stable, flexible, and reliable cloud data lake without any technical knowledge. All of your company data can be brought together, explored with SQL, and visualized with your favorite BI tool. Dataleyk will modernize your data warehouse. Our cloud-based data platform is capable of handling both structured and unstructured data. Data is an asset. Dataleyk, a cloud-based data platform, encrypts all data and offers data warehousing on-demand. Zero maintenance may not be an easy goal. It can be a catalyst for significant delivery improvements, and transformative results.

Businesses struggle to find answers as data volumes increase faster than ever. Teradata Vantage™, solves this problem. Vantage uses 100 per cent of the data available to uncover real-time intelligence at scale. This is the new era in Pervasive Data Intelligence. All data across the organization is available in one place. You can access it whenever you need it using preferred languages and tools. Start small and scale up compute or storage to areas that have an impact on modern architecture. Vantage unifies analytics and data lakes in the cloud to enable business intelligence. Data is growing. Business intelligence is becoming more important. Four key issues that can lead to frustration when using existing data analysis platforms include: Lack of the right tools and supportive environment required to achieve quality results. Organizations don't allow or give proper access to the tools they need. It is difficult to prepare data.

Many customers of Amazon Web Services (AWS), require data storage and analytics solutions that are more flexible and agile than traditional data management systems. Data lakes are a popular way to store and analyze data. They allow companies to manage multiple data types, from many sources, and store these data in a central repository. AWS Cloud offers many building blocks to enable customers to create a secure, flexible, cost-effective data lake. These services include AWS managed services that allow you to ingest, store and find structured and unstructured data. AWS offers the data solution to support customers in building data lakes. This is an automated reference implementation that deploys an efficient, cost-effective, high-availability data lake architecture on AWS Cloud. It also includes a user-friendly console for searching for and requesting data.

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.

Our SHREWD Platform tools, open APIs and SHREWD Platform tools allow you to harness your entire system's data. SHREWD Platform is the platform that integrates and collects data from the SHREWD modules. The tools combine data and store it in our secure, UK-based database lake. The SHREWD modules and an API can access this data to transform it into meaningful information using targeted functions. SHREWD Platform can access data in almost any format. This includes analog data in spreadsheets and digital systems via APIs. Open APIs allow third-party connections to the data lake. SHREWD Platform is an operational data layer that provides a single source for the truth in real time. It allows SHREWD modules provide intelligent insights and managers and key decision-makers to take appropriate action at the right moment.

Varada's adaptive and dynamic big data indexing solution allows you to balance cost and performance with zero data-ops. Varada's big data indexing technology is a smart acceleration layer for your data lake. It remains the single source and truth and runs in the customer's cloud environment (VPC). Varada allows data teams to democratize data. It allows them to operationalize the entire data lake and ensures interactive performance without the need for data to be moved, modelled, or manually optimized. Our ability to dynamically and automatically index relevant data at the source structure and granularity is our secret sauce. Varada allows any query to meet constantly changing performance and concurrency requirements of users and analytics API calls. It also keeps costs predictable and under control. The platform automatically determines which queries to speed up and which data to index. Varada adjusts the cluster elastically to meet demand and optimize performance and cost.

BryteFlow creates the most efficient and automated environments for analytics. It transforms Amazon S3 into a powerful analytics platform by intelligently leveraging AWS ecosystem to deliver data at lightning speed. It works in conjunction with AWS Lake Formation and automates Modern Data Architecture, ensuring performance and productivity.

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.

A single storage platform can eliminate data silos. Tiered storage and policy management can help you reduce costs. Azure Active Directory (Azure AD), and role-based access control(RBAC) can authenticate data. You can also help protect your data with advanced threat protection and encryption at rest. Flexible mechanisms provide protection for data access, encryption, network-level control, and more. Highly secure. A single storage platform that supports all the most popular analytics frameworks. Cost optimization through independent scaling of storage, compute, lifecycle management and object-level Tiering. With the Azure global infrastructure, you can meet any capacity requirement and manage data with ease. Large-scale analytics queries run at high performance.

BiGENIUS automates all phases of analytic data management solutions (e.g. data warehouses, data lakes and data marts. thereby allowing you to turn your data into a business as quickly and cost-effectively as possible. Your data analytics solutions will save you time, effort and money. Easy integration of new ideas and data into data analytics solutions. The metadata-driven approach allows you to take advantage of new technologies. Advancement of digitalization requires traditional data warehouses (DWH) as well as business intelligence systems to harness an increasing amount of data. Analytical data management is essential to support business decision making today. It must integrate new data sources, support new technologies, and deliver effective solutions faster than ever, ideally with limited resources.

AI-powered self-service platform for advanced analytics. Without programming, connect data sources and create visualizations. Cloud native advanced analytics platform that delivers high-quality data supply, intelligent real-time analysis across enterprises without the need for programming. Connect data sources in different formats. Allows for the identification of root causes. Reduce cycle time from source to destination Analytics without programming knowledge Real-time data refresh on the move Connect any data source, stream data in real-time or at a defined frequency to the data lake, and visualize them in interactive search engine-based dashboards. With the power of the search engine and advanced visualization, you can perform predictive, prescriptive and descriptive analytics from one platform. No need to use traditional technology to view data in different visualization formats. Bizintel360 visualization allows you to slice, dice and combine data with different mathematical computations.

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.

Customers can deploy Hadoop clusters in any size using Oracle Big Data Service. VM shapes range from 1 OCPU up to a dedicated bare-metal environment. Customers can choose between high-performance block storage or cost-effective block store, and can grow and shrink their clusters. Create Hadoop-based data lakes quickly to expand or complement customer data warehouses and ensure that all data can be accessed and managed efficiently. The included notebook supports R, Python, and SQL. Data scientists can query, visualize, and transform data to build machine learning models. Transfer customer-managed Hadoop clusters from a managed cloud-based service to improve resource utilization and reduce management costs.

Secure and manage the data lifecycle, from Edge to AI in any cloud or data centre. Operates on all major public clouds as well as the private cloud with a public experience everywhere. Integrates data management and analytics experiences across the entire data lifecycle. All environments are covered by security, compliance, migration, metadata management. Open source, extensible, and open to multiple data stores. Self-service analytics that is faster, safer, and easier to use. Self-service access to multi-function, integrated analytics on centrally managed business data. This allows for consistent experiences anywhere, whether it is in the cloud or hybrid. You can enjoy consistent data security, governance and lineage as well as deploying the cloud analytics services that business users need. This eliminates the need for shadow IT solutions.

StarTree Cloud is a fully-managed user-facing real-time analytics Database-as-a-Service (DBaaS) designed for OLAP at massive speed and scale. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

The Unified Analytics Warehouse. The Unified Analytics Warehouse is the best place to find high-performing analytics and machine learning at large scale. Tech research analysts are seeing new leaders as they strive to deliver game-changing big data analytics. Vertica empowers data-driven companies so they can make the most of their analytics initiatives. It offers advanced time-series, geospatial, and machine learning capabilities, as well as data lake integration, user-definable extensions, cloud-optimized architecture and more. Vertica's Under the Hood webcast series allows you to dive into the features of Vertica - delivered by Vertica engineers, technical experts, and others - and discover what makes it the most scalable and scalable advanced analytical data database on the market. Vertica supports the most data-driven disruptors around the globe in their pursuit for industry and business transformation.

SAP HANA is an in-memory database with high performance that accelerates data-driven decision-making and actions. It supports all workloads and provides the most advanced analytics on multi-model data on premise and in cloud.

Panoply makes it easy to store, sync and access all your business information in the cloud. With built-in integrations to all major CRMs and file systems, building a single source of truth for your data has never been easier. Panoply is quick to set up and requires no ongoing maintenance. It also offers award-winning support, and a plan to fit any need.

Hydrolix is a streaming lake of data that combines decoupled archiving, indexed searching, and stream processing for real-time query performance on terabyte scale at a dramatically lower cost. CFOs love that data retention costs are 4x lower. Product teams appreciate having 4x more data at their disposal. Scale up resources when needed and down when not. Control costs by fine-tuning resource consumption and performance based on workload. Imagine what you could build if you didn't have budget constraints. Log data from Kafka, Kinesis and HTTP can be ingested, enhanced and transformed. No matter how large your data, you will only get the data that you need. Reduce latency, costs, and eliminate timeouts and brute-force queries. Storage is decoupled with ingest and queries, allowing them to scale independently to meet performance and cost targets. Hydrolix's HDX (high-density compress) reduces 1TB to 55GB.

Data management and analytics platform that addresses data challenges and enables real-time decision making. DataLux includes plug-and-play adaptors that allow for the aggregation and visualization of large data sets. The data lake can be used to prevent new innovations. You can store data and make it available for data modeling. Containeristion can be used to create portable applications in a public, private, or on-premise cloud. Multiple time-series and inferred data can be combined, such as stock exchange tick data and stock market policy actions. You can also combine related and cross-industry data to extract causal information about stock market, macroeconomics, and other factors. By providing insights and guiding key decisions for product improvement, business decisions can be made. You can conduct interdisciplinary A/B tests across product design, engineering, and product development from ideation to decision-making.

Arcadia Data is the first native Hadoop and cloud (big) visual analytics and BI platform that provides the scale, performance and agility business users require for real-time and historical insight. Arcadia Enterprise, its flagship product, was created from the beginning for big data platforms like Apache Hadoop, Apache Spark and Apache Kafka. It can be used on-premises or in the cloud. Arcadia Enterprise uses artificial intelligence (AI), machine learning (ML) to streamline the self-service analytics process. It offers search-based BI, visualization recommendations, and a streamlined self-service analytics process. It provides real-time, high definition insights in use cases such as data lakes, cybersecurity, and customer intelligence. Some of the most recognizable brands in the world use Arcadia Enterprise, including Procter & Gamble and Nokia, Procter & Gamble and Citibank, Nokia, Royal Bank of Canada. Kaiser Permanente, HPE and Neustar.

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.

Starburst allows you to make better decisions by having quick access to all of your data. Your company has more data than ever, but your data teams are still waiting to analyze it. Starburst gives your data teams quick and accurate access to more data. Starburst Enterprise, a fully supported, production-tested, enterprise-grade distribution for open source Trino (formerly Presto®, SQL), is now available. It increases performance and security, while making it easy for you to deploy, connect, manage, and manage your Trino environment. Starburst allows your team to connect to any source of data, whether it's on-premise, in a cloud, or across a hybrid cloud environment. This allows them to use the analytics tools they already love and access data that lives anywhere.

Trino is an engine that runs at incredible speeds. Fast-distributed SQL engine for big data analytics. Helps you explore the data universe. Trino is an extremely parallel and distributed query-engine, which is built from scratch for efficient, low latency analytics. Trino is used by the largest organizations to query data lakes with exabytes of data and massive data warehouses. Supports a wide range of use cases including interactive ad-hoc analysis, large batch queries that take hours to complete, and high volume apps that execute sub-second queries. Trino is a ANSI SQL query engine that works with BI Tools such as R Tableau Power BI Superset and many others. You can natively search data in Hadoop S3, Cassandra MySQL and many other systems without having to use complex, slow and error-prone copying processes. Access data from multiple systems in a single query.

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

Even the most data-driven organizations are often challenged by the increasing volume, velocity, and variety of data. As analytics expectations rise, infrastructure, time, and people resources are becoming increasingly scarce. Xurmo addresses this problem with an easy-to use, self-service product. You can configure and ingest all data using one interface. Xurmo can consume any type of structured or unstructured data and bring it to analysis. Xurmo will do the heavy lifting for you and help you to create intelligence. Xurmo provides interactive support, from building analytical models to deploying them as an automation mode. Automate intelligence even from complex, dynamically changing data. Xurmo analytical models can be configured and deployed in an automation mode across different data environments.

You can load your data into Hadoop or data lakes. Prepare it for visualizations, advanced analytics, reports and reporting - all from the data lakes. You can do it all yourself, fast and easily. It makes it easy to access, transform, and manage data stored in Hadoop/data lakes using a web-based interface. This reduces training requirements. It was designed from the ground up to manage large amounts of data in Hadoop and data lakes. It is not repurposed or adapted from existing IT-focused tools. You can group multiple directives together to run simultaneously, or one after another. The exposed Public API allows you to schedule and automate directives. Allows you to share or secure directives. These directives can be called from SAS Data Integration Studio. This combines technical and non-technical user activities. Included directives: casing, gender, pattern analysis, field extract, match-merge, cluster-survive. For better performance, profiling runs parallel on the Hadoop cluster.

We have created a revolutionary platform for big data that collects all information about a business and provides a single source to make informed decisions. Each music business has hundreds upon hundreds of data sources. They are scattered and siloed. Our platform connects them to create a foundation of high-quality data that can be used in all aspects of music business operations. Record labels and agencies need a sophisticated data management system and governance system to ensure that their data is always available, relevant, and easily accessible. This will allow them to work efficiently and securely, as well as uncover valuable insights that no one else can. Machine learning is used to tag data as they are added to Wavo's Big Data Platform. This makes it easy to drill-down and access important information. This allows everyone in a music industry to activate and deliver business-ready data that is backed up and organized for immediate benefit.

Qlik Data Integration platform automates the process for providing reliable, accurate and trusted data sets for business analysis. Data engineers are able to quickly add new sources to ensure success at all stages of the data lake pipeline, from real-time data intake, refinement, provisioning and governance. This is a simple and universal solution to continuously ingest enterprise data into popular data lake in real-time. This model-driven approach allows you to quickly design, build, and manage data lakes in the cloud or on-premises. To securely share all your derived data sets, create a smart enterprise-scale database catalog.

When you have the expertise of an enterprise partner combined with a scalable, easy-to-use data management suite, you can take back control of your data, access it from anywhere, ensure security and compliance, and unlock its power to grow your business. Why Use Sesame Software? Relational Junction builds, populates, and incrementally refreshes your data automatically. Enhance Data Quality - Convert data from multiple sources into a consistent format – leading to more accurate data, which provides the basis for solid decisions. Gain Insights - Automate the update of information into a central location, you can use your in-house BI tools to build useful reports to avoid costly mistakes. Fixed Price - Avoid high consumption costs with yearly fixed prices and multi-year discounts no matter your data volume.

You can accelerate discovery by giving your business access to analytics-ready data on demand. This will help you get answers faster. Qlik Catalog is an enterprise-scale data catalog that speeds up the organization, preparation, delivery, and analysis of trusted, actionable data. It takes days, not months, to create and maintain a profile, organize, prepare, and deliver data. Qlik Catalog creates a secure enterprise-scale catalog that contains all data available for analytics in your organization, regardless of where it is located. The powerful, automated data preparation and metadata tools simplify the transformation of raw data into data assets that are ready for analysis. Business users have one place to go to for all their data needs. They can search, understand, and use any source of enterprise data to gain insight. To simplify and speed up the process, automatically profile and document the exact structure, content, and quality of your data with built-in data loaders. Create a Smart Data Catalog to document every aspect of your data.

GeoSpock DB - The space-time analytics database - allows data fusion in the connected world. GeoSpockDB is a unique cloud-native database that can be used to query for real-world applications. It can combine multiple sources of Internet of Things data to unlock their full potential, while simultaneously reducing complexity, cost, and complexity. GeoSpock DB enables data fusion and efficient storage. It also allows you to run ANSI SQL query and connect to analytics tools using JDBC/ODBC connectors. Users can perform analysis and share insights with familiar toolsets. This includes support for common BI tools such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™, as well as Data Science and Machine Learning environments (including Python Notebooks or Apache Spark). The database can be integrated with internal applications as well as web services, including compatibility with open-source visualisation libraries like Cesium.js and Kepler.

lakeFS allows you to manage your data lake in the same way as your code. Parallel pipelines can be used for experimentation as well as CI/CD of your data. This simplifies the lives of data scientists, engineers, and analysts who work in data transformation. lakeFS is an open-source platform that provides resilience and manageability for object-storage-based data lakes. lakeFS allows you to build repeatable, atomic, and versioned data lakes operations. This includes complex ETL jobs as well as data science and analysis. lakeFS is compatible with AWS S3, Azure Blob Storage, and Google Cloud Storage (GCS). It is API compatible to S3 and seamlessly integrates with all modern data frameworks like Spark, Hive AWS Athena, Presto, AWS Athena, Presto, and others. lakeFS is a Git-like branching/committing model that can scale to exabytes by using S3, GCS, and Azure Blob storage.

Tugger swiftly and securely pulls your data out of your business systems and into data analytics and visualisation tools such as Power BI and Tableau. This enables you to produce state of the art interactive reports. Once your data has been copied across, Tugger also gets you set up with key business reports for a complete end-to-end solution. This saves you masses of time. Tugger is a no code solution that makes your life easier by removing the need for any manual API integrations and reduces the risk of skewed data. No technical knowledge is required and all users get access to Tugger's excellent support team. Tugger provides data connectors for HubSpot, Harvest, Microsoft Teams, JIRA, GitHub, simPRO and more.

Somnoware's software for managing sleep labs allows you to diagnose and manage patients in the way that you choose. You can use any major testing device. Unify all PAP data on one secure platform. Automate patient engagement. You can customize dashboards and reports. All the tools you need in one place. The Somnoware Diagnostic Module automates the process for conducting diagnostic tests. Scheduling is easy, inventory is always available, physicians have instant access to test results, ordering therapy is a simple one-click process. Somnoware Diagnostics, a cloud-based platform that enhances sleep and respiratory care management, is available. The platform facilitates data flow between disparate medical devices. It allows screening and faster diagnosis, which leads to better treatment outcomes. SOC 2 is a security platform that is often used to comply HIPAA and the GDPR. These standards are further evidence of our commitment to data security.

BIRD Analytics is a lightning fast, high-performance, full-stack data management and analytics platform that generates insights using agile BI/ ML models. It covers all aspects of data ingestion, transformation, storage, modeling, analysis, and store data on a petabyte scale. BIRD offers self-service capabilities via Google type search and powerful ChatBot integration

Doolytic is a leader in big data discovery, the convergence data discovery, advanced analytics and big data. Doolytic is bringing together BI experts to revolutionize self-service exploration of large data. This will unleash the data scientist in everyone. doolytic is an enterprise solution for native big data discovery. doolytic is built on open-source, scalable technologies that are best-of-breed. Lightening performance on billions and petabytes. Structured, unstructured, and real-time data from all sources. Advanced query capabilities for experts, Integration with R to enable advanced and predictive applications. With Elastic's flexibility, you can search, analyze, and visualize data in real-time from any format or source. You can harness the power of Hadoop data lakes without any latency or concurrency issues. doolytic solves common BI issues and enables big data discovery without clumsy or inefficient workarounds.

ROBIN is the first hyper-converged Kubernetes platform in the industry for big data, databases and AI/ML. The platform offers a self-service App store experience to deploy any application anywhere. It runs on-premises in your private cloud or in public-cloud environments (AWS, Azure and GCP). Hyper-converged Kubernetes combines containerized storage and networking with compute (Kubernetes) and the application management layer to create a single system. Our approach extends Kubernetes to data-intensive applications like Hortonworks, Cloudera and Elastic stack, RDBMSs, NoSQL database, and AI/ML. Facilitates faster and easier roll-out of important Enterprise IT and LoB initiatives such as containerization and cloud-migration, cost consolidation, productivity improvement, and cost-consolidation. This solution addresses the fundamental problems of managing big data and databases in Kubernetes.

What is Presto? Presto is a distributed, federated SQL query engine that runs on multiple machines. It allows interactive, ad-hoc analysis on large quantities of data. You can run Presto SQL queries against your data. PrestoDB allows you to query data wherever it is located, including Hive and AWS S3, Hadoop and Cassandra, as well as relational databases, NoSQL database, or proprietary data stores. Presto is an open-source engine that allows users to access multiple sources of data, allowing them to perform analytics across the entire organization. A complete Presto installation requires a coordinator and multiple workers. Queries are sent from clients such as the Presto client to the coordinator. The coordinator analyzes, plans, and executes Presto queries.

Gravwell is an all you can ingest data fusion platform that allows for complete context and root cause analysis for security and business data. Gravwell was created to provide machine data benefits to all customers, large or small, binary or text, security or operational. An analytics platform that can do things you've never seen before is possible when experienced hackers team up with big data experts. Gravwell provides security analytics that go beyond log data to industrial processes, vehicle fleets, IT infrastructure or all of it. Do you need to track down an access breach? Gravwell can run facial recognition machine-learning against camera data to identify multiple subjects who enter a facility with one badge-in. Gravwell can also correlate building access logs. We are here to help people who require more than text log searching and want it sooner than they can afford.