Alternatives to Sifflet

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.

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.

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.

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.

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.

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.

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.

Your metadata can be discovered, documented and managed. Dataedo has multiple automated metadata scanners. These scanners connect to different database technologies, extract data structures, and then load them into the metadata repository. In just a few clicks you can create a catalog of all your data and then describe each element. With business-friendly aliases, decrypt column and table names and provide meaning and purpose to data assets with descriptions and custom fields. To find out what data is stored in your data asset, you can use sample data. Make sure you have a better understanding of the data before you use it. Data profiling can help ensure high quality data. Data profiling allows everyone to have access to data knowledge. A lightweight, on-premises data catalogue can help you build data literacy, democratize data, and empower your employees to make better data use. A data catalog can help you increase data literacy.

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.

Secoda AI can help you generate documentation and queries from your metadata. This will save your team hundreds of hours of tedious work. Secoda AI will also generate documentation and queries based on your metadata. This will save your team hundreds of tedious hours and redundant data requests. Search across all columns, dashboards and metrics, as well as tables, dashboards and tables. AI-powered searches allow you to ask any question and receive a contextual response quickly. Answer questions. Our API allows you to integrate data discovery into your workflow, without disrupting the flow. Perform bulk updates, tag PII, manage tech debt and more. Eliminate manual errors and have complete trust in your knowledge base.

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.

DataGalaxy’s all-in one data catalog provides out-of-the box actionability, with fully-customizable features, visualization tools, AI integration, to give business teams a way to document, link and track their metadata assets. The Data Catalog 360deg platform's user-centric approach is dedicated to metadata management, knowledge sharing, and mapping. This helps your organization manage data in the way that you want. A data catalog allows employees from different teams to collaborate by using homogeneous, centralized data sets. Our data catalog provides clarity for data definitions, synonyms and essential business attributes. It also includes a semantic layer to help all users understand and leverage data. If you are looking for answers on a specific metadata, the data catalog will identify 360deg data experts and owners. This will empower your team by facilitating collaboration.

Atlas is a flexible and extensible set core foundational governance services that enable enterprises to efficiently and effectively meet their compliance requirements within Hadoop. It also allows integration with the entire enterprise data ecosystem. Apache Atlas offers open metadata management and governance capabilities that allow organizations to create a catalog of their data assets, classify, govern and provide collaboration capabilities around these assets for data scientists, analysts, and the data governance group. Pre-defined types to manage various Hadoop and non Hadoop metadata. Ability to create new types to manage metadata. Types can inherit from other types, and can have simple attributes, complex attributes, and object references. Type instances, also known as entities, are able to capture metadata object details and their relationships. REST APIs allow for easier integration with types and instances.

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.

Blindata is a comprehensive Data Governance program that includes all functions. Data Catalog, Data Lineage & Business Glossary provide a complete and integrated view of your Data. Data Classification gives data a semantic meaning, while Data Quality Modules, Issue Management and Data Stewardship modules increase the reliability and trust of data. Privacy compliance can also be facilitated by specific features. Registry of processing activities, central management of privacy notes, consent registry with Blockchain integration. Blindata Agent is able to connect to multiple data sources and collect metadata, such as data structures (Tables Views Fields ...), data Quality metrics, reverse lineage etc.). Blindata's modular architecture is entirely API-based, allowing for systematic integration with business systems of the highest importance (DBMS, Active Directory e-commerce and Data Platforms). Blindata can be purchased as a SaaS or installed "on Premise", or it can be purchased from AWS Marketplace.

Talend Data Catalog provides your organization with a single point of control for all your data. Data Catalog provides robust tools for search, discovery, and connectors that allow you to extract metadata from almost any data source. It makes it easy to manage your data pipelines, protect your data, and accelerate your ETL process. Data Catalog automatically crawls, profiles and links all your metadata. Data Catalog automatically documents up to 80% of the data associated with it. Smart relationships and machine learning keep the data current and up-to-date, ensuring that the user has the most recent data. Data governance can be made a team sport by providing a single point of control that allows you to collaborate to improve data accessibility and accuracy. With intelligent data lineage tracking and compliance tracking, you can support data privacy and regulatory compliance.

erwin Data Intelligence, or erwin DI, combines data literacy and data catalog capabilities to provide greater awareness and access to data assets, guidance on how to use them, and guardrails to ensure that data policies and best practice are followed. Automatically extract, transform, and feed metadata from a variety of data sources, operational process, and data models into one central catalog. It is then made accessible and understandable through role-based, contextual views. This allows stakeholders to make strategic decisions based upon accurate insights. erwin DI supports enterprise information governance, digital transformation, and any other effort that relies upon data to achieve positive outcomes. You can schedule ongoing scans of metadata from a wide range of data sources. You can easily map data elements from source and target, including data moving, and harmonize data integration across platforms. Data consumers can easily identify and find data that is relevant to their roles.

The Collibra Data Intelligence Cloud offers a best-in class catalog, flexible governance and continuous quality. It also has built-in privacy. A best-in-class data catalogue that supports your users includes embedded governance, privacy, and quality. You can raise the bar by ensuring that teams can quickly access, understand, and access data from all sources, including business applications and data science tools, in one central location. Your data deserves privacy. Automate, centralize and guide workflows to encourage collaboration and operationalize privacy. Collibra Data Lineage gives you the complete story about your data. Automatically map relationships between applications, systems, and reports to provide a context rich view of the enterprise. Focus on the data that you are most concerned about and make sure it is accurate, complete, and trustworthy.

Although your organization understands the value of data, and how it must be accessible to business users for maximum impact, enterprise data governance can make it difficult to trust, understand, or find that data. Data360 Govern, an enterprise data governance, metadata, and catalog management solution, gives you confidence in your data's quality, value, and trustworthiness. It automates governance tasks and stewardship tasks, helping you to answer critical questions about your data's origin, use, meaning, ownership and quality. Data360 Govern allows you to make faster decisions about data usage and management, foster collaboration across your organization, and give users the ability to get the answers they require - whenever they need them. Transparency into your company's data landscape allows you to track the most critical data that aligns with your business goals.

View the impact of data issues in real time without running SQL. We analyze your logs to identify freshness anomalies and volume, schema changes, pipeline errors and their impact on your business. Masthead monitors each table, script, process and dashboard in your data warehouse, as well as the connected BI tools, for anomalies. It alerts data teams in real-time if data failures happen. Masthead shows data anomalies, pipeline errors and their implications on data consumers. Masthead maps lineage data issues, so you can troubleshoot in minutes, not hours. It was a game changer for us to get a comprehensive overview of all processes within GCP without having to give access our data. It saved us time and money. You can now see the cost of every pipeline in your cloud, irrespective of whether it is ETL. Masthead has AI-powered recommendations that can help you optimize your queries and models. Masthead can be connected to your data warehouse in 15 minutes.

No more data catalog ghost cities. Acryl Cloud accelerates time-to-value for data producers through Shift Left practices and an intuitive user interface for data consumers. Continuously detect data-quality incidents in real time, automate anomaly detecting to prevent breakdowns, and drive quick resolution when they occur. Acryl Cloud supports both pull-based and push-based metadata ingestion to ensure information is reliable, current, and definitive. Data should be operational. Automated Metadata Tests can be used to uncover new insights and areas for improvement. They go beyond simple visibility. Reduce confusion and speed up resolution with clear asset ownership and automatic detection. Streamlined alerts and time-based traceability are also available.

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

End-to-end DataOps built upon an agile platform that protects and improves your data assets. Arena is the leading augmented data management platform. Our active data catalog allows for self-service data enrichment to control complex data environments. You can create custom workflows to increase the reliability and accuracy of each data set. Machine-learning can be used to identify and align master assets for better data decisions. Superior security is assured with complete lineage, including detailed visualizations and masking. Data management is easy with Arena. Arena can catalog your data from any location. Our extensible connections allow for analytics across all your preferred tools. Overcome data sprawl challenges with our software. Our software is designed to drive business and analytics success, while also providing the controls and extensibility required in today's multicloud data complexity.

Tableau Catalog is a benefit for everyone. Tableau Catalog provides a complete view of the data and how it connects to the analytics in Tableau. This increases trust and discoverability for IT and business users. Tableau Catalog makes it easy to communicate changes to the data, review dashboards, or search for the right data for analysis. Tableau Catalog automatically ingests all data assets in your Tableau environment into a single central list. There is no need to create an index schedule or connect. You can quickly see all of your files, tables, and databases in one location. Migration of databases, deprecating fields or adding a column to a table can all have potential impacts on your environment. Lineage and impact analysis allows you to see not only the upstream and downstream implications of assets but also who will be affected.

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

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.

The new world of data means that you can spend more time looking at data than you are analyzing it. Azure Data Catalog is an enterprise-wide data catalog that makes data asset discovery easy. It is a fully managed service that allows you, from analyst to data scientist, to use it to register, enrich, discover and understand data sources. You can work with data using the tool you prefer. Data Catalog allows you to find the data you need, and you can use it in any tool you choose. Data Catalog ensures that your data is always available. It makes it easy to find and use the data you need, and provides an intuitive user interface. Increase adoption and continuous value generation across your data ecosystem. Data Catalog provides tips, tricks, as well as unwritten rules that can be used to create an environment where everyone can benefit. Data Catalog makes it possible for everyone to contribute. Democratize data asset discovery.

Data knowledge management platform that allows teams to simplify data discovery and understanding with the ultimate goal to be able to trust their data. Stop costly mistakes and misreporting analytics today!

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

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.

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.

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.

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.

Identify code issues and optimize code in real-time. Prevent data incidents before deployment. Manage code changes that impact data from the operational database all the way to the dashboard. Data lineage is automated, allowing for analysis of every dependency, from the operational database to the reporting layer. Foundational automates the enforcement of data contracts by analyzing each repository, from upstream to downstream, directly from the source code. Use Foundational to identify and prevent code and data issues. Create controls and guardrails. Foundational can be configured in minutes without requiring any code changes.

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.

You can scan and index metadata, discover and profile information, and provide detailed lineage across tens to millions of data sets. To maximize data reuse and data value, classify and organize data assets in any environment. Automate scanning across multiple cloud platforms, BI tools and ETL tools; and data types. AI-powered domain discovery, data similarities, business term associations, recommendations, and recommendation making are possible. You can track data movement from high-level system views through to fine column-level lineage and get detailed impact analysis. The Data Asset Analytics dashboard allows you to see asset usage, enrichment, collaboration. You can view data quality rules, scorecards and metric groups in context. You can tap into shared data knowledge through certifications, ratings, reviews, a Q&A forum, and change notifications. Informatica stands out from the rest with its extensive range of enterprise-grade data management products.

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.

You can unify your data catalog, reduce communication overhead, and enable quality control for any employee of your company without having to deploy or install anything. Rudol is a data platform that helps companies understand all data sources, regardless of where they are from. It reduces communication in reporting processes and urgencies and allows data quality diagnosis and issue prevention for all company members. Each organization can add data sources from rudol's growing list of providers and BI tools that have a standardized structure. This includes MySQL, PostgreSQL. Redshift. Snowflake. Kafka. S3*. BigQuery*. MongoDB*. Tableau*. PowerBI*. Looker* (*in development). No matter where the data comes from, anyone can easily understand where it is stored, read its documentation, and contact data owners via our integrations.

Data intelligence can transform data chaos into data value. Disjointed data assets can be connected, discovered, enriched, and orchestrated to provide actionable business insights at an enterprise scale. SAP Data Intelligence provides a comprehensive data management solution. It is the data orchestration layer within SAP's Business Technology Platform. It transforms distributed data into vital data insights and delivers innovation at scale. Integrate across the IT landscape to provide intelligent, relevant and contextual insights for your users. Integrate and orchestrate large data volumes and streams at scale. Machine learning enables you to streamline, operationalize, manage, and govern innovation. Comprehensive metadata management rules optimize governance and reduce compliance risk. Disjointed data assets can be connected, discovered, enriched, and orchestrated to provide actionable business insights at enterprise level.

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

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

Glasnostic inserts itself agentlessly into the network data pathway, observes interaction patterns among services, detects anomalies and responds in real-time with predictable and effective control primitives. If you are not connected to the action, visibility is useless. Glasnostic allows engineers to respond in real-time to system behavior and proactively. Glasnostic inserts transparent controllers in the network data plane. These controllers act as a brain within the wire that responds to and detects behaviors in real time. Interaction metrics are sent from the control plane to the control plane for storage and anomaly detection. They can also be used for manual or automated control. Glasnostic integrates with all major cloud technologies. It can also integrate with existing tools, from AIOps to workflows and security tools via webhooks and APIs. Glasnostic can work with all major technology stacks. System behaviors can be viewed holistically, uniformly, everywhere.

Anomalo helps you get ahead of data issues by automatically detecting them as soon as they appear and before anyone else is impacted. -Depth of Checks: Provides both foundational observability (automated checks for data freshness, volume, schema changes) and deep data quality monitoring (automated checks for data consistency and correctness). -Automation: Use unsupervised machine learning to automatically identify missing and anomalous data. -Easy for everyone, no-code UI: A user can generate a no-code check that calculates a metric, plots it over time, generates a time series model, sends intuitive alerts to tools like Slack, and returns a root cause analysis. -Intelligent Alerting: Incredibly powerful unsupervised machine learning intelligently readjusts time series models and uses automatic secondary checks to weed out false positives. -Time to Resolution: Automatically generates a root cause analysis that saves users time determining why an anomaly is occurring. Our triage feature orchestrates a resolution workflow and can integrate with many remediation steps, like ticketing systems. -In-VPC Development: Data never leaves the customer’s environment. Anomalo can be run entirely in-VPC for the utmost in privacy & security

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.

Kensu monitors data usage throughout the day in real-time. This allows your team to prevent data incidents. It is important to understand how you use your data, not just the data. A single comprehensive view allows you to analyze data quality and lineage. Real-time insight into data usage across all of your systems, projects, or applications. Instead of relying on ever-increasing numbers of repositories, monitor data flow. With catalogs, glossaries and incident management systems, share lineages, schemas, and quality information. To prevent data catastrophes from spreading, identify the root causes of complex data issues at a glance. You can generate notifications about specific data events and their context. Learn how data was collected, copied, and modified by any application. Analyze historical data information to detect anomalies. Use historical data information and leverage lineage to determine the cause.

You can innovate faster in the cloud, improve user experience and future-proof applications. Splunk is designed for cloud-native enterprises and helps you solve current problems. Splunk helps you detect any problem before it becomes a customer problem. Our AI-driven Directed Problemshooting reduces MTTR. Flexible, open-source instrumentation eliminates lock-in. Optimize performance by seeing all of your application and using AI-driven analytics. You must observe everything in order to deliver an excellent end-user experience. NoSample™, full-fidelity trace ingestion allows you to leverage all your trace data and identify any anomalies. Directed Troubleshooting reduces MTTR to quickly identify service dependencies, correlations with the underlying infrastructure, and root-cause errors mapping. You can break down and examine any transaction by any dimension or metric. You can quickly and easily see how your application behaves in different regions, hosts or versions.

The most widely used observability platform, built on the ELK Stack, is the best choice. It converges silos and delivers unified visibility and actionable insight. All your observability data must be in one stack to effectively monitor and gain insight across distributed systems. Unify all data from the application, infrastructure, user, and other sources to reduce silos and improve alerting and observability. Unified solution that combines unlimited telemetry data collection with search-powered problem resolution for optimal operational and business outcomes. Converge data silos with the ingesting of all your telemetry data from any source, in an open, extensible and scalable platform. Automated anomaly detection powered with machine learning and rich data analysis can speed up problem resolution.

You can instantly see the order in your complex data world and know exactly where to find answers. Datakin automatically tracks data lineage and displays your entire data ecosystem as a rich visual graph. It clearly shows the upstream and downstream relationships of each dataset. The Duration tab summarizes the job's performance and its upstream dependencies in a Gantt-style graph. This makes it easy to identify bottlenecks. The Compare tab allows you to see how your jobs and data have changed over time. Sometimes jobs that run well can produce poor output. The Quality tab shows you the most important data quality metrics and how they change over time. This makes anomalies easily visible. Datakin allows you to quickly identify the root cause of problems and prevent them from happening again.

Visualize data lineage automatically extracting data flow data source to target. Data lineage management software that automatically collects and analyzes mission-critical data. It also visualizes data flow and derivation rules from data source to target. Data Lineage refers to the flow of data between the source and the target. Tracking Data Lineage is about understanding the flow and derivation rules of data processed, transformed, and used. Multi-tier column-level data lineage graph and list, from source to destination. Drill down data lineage at the business system, column and table levels. Provide parsers to support analysis of Big Data technologies and various environments. Our patented technology allows for path sensitive dynamic string analysis and data flow analysis within programs.

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.