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Run Crosser Nodes with advanced analytics in any distributed Edge, On-premise or Cloud. Managed by the Crosser Control Center.
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Event Processing, Stream Analytics, ETL and Integration in one easy-to-use platform.
A SaaS service for designing, deploying and monitoring your data pipelines.
The low-code drag-and-drop design studio supporting +800 integrations and +100 modules for transforming data and applying advanced processing logic.
The lightweight and high performing runtime that you install as a Docker container or as a native Windows service. Anywhere.
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Data Observability of all your data flows and integrations.
Dynamic deployment of your data flows and custom code.
Event-driven Data Lake and Data Warehouse Integration.
Integrate streams, on-prem applications, SaaS apps, files and API's.
Make your applications event-driven and modern for real-time experiences.
Unite your OT & IT teams with one modern platform.
Integrate everything on the shop-floor in real-time.
Pre-process data in the edge with smart actions.
The Intelligent Bridge between Industrial and Cloud.
Seamlessly implement UNS and simplify your data stack.
Integrate directly to Azure storage from the edge or as an alternative to Azure ETL Tools.
An alternative to AWS ETL tools or integrate directly to AWS storage from the edge.
Integrate directly to GCP storage from the edge or cloud. An alternative to GCP ETL tools.
Stream ready-to-use data directly to Snowflake from any source and location.
Stream ready-to-use data directly to Databricks from any source and location.
Explore use cases for Stream Analytics, ETL/ELT, Event Processing, and Data Engineering.
Use cases for event-driven data integration and workflow automation.
Edge Streaming Analytics, Integration and Automation use cases for Industrial IoT and Industry 4.0.
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Glossary
Articles
What is AI Agent?
An AI Agent is an autonomous system or software that uses artificial intelligence techniques to perform tasks, make decisions, and solve problems without direct human intervention.
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What is AI Ethics??
Artificial Intelligence (AI) Ethics refers to the moral considerations surrounding the development and deployment of AI technologies.
What is Anomaly Detection?
Anomaly detection is the process of identifying unusual patterns or outliers in data that do not conform to expected behavior. It is commonly used for fraud detection, system monitoring, and cybersecurity.
What is Artificial Neural Networks (ANNs)?
ANNs are a class of machine learning algorithms inspired by the human brain’s structure. These networks consist of layers of interconnected nodes, or "neurons," and are used for tasks like image recognition, speech processing, and more.
What is Batch Processing?
Batch processing refers to the processing of a large set of data or tasks in a non-interactive mode, typically in a scheduled time frame. It is a way of processing large volumes of data, where a large number of transactions or data records are collected over a period of time, and then processed together in a single batch, rather than processing each transaction or data record individually in real-time.
What is Big Data?
Big data refers to the large and complex sets of data that organizations need to process and analyze. It is characterized by its volume, variety, and velocity. Volume refers to the sheer amount of data that organizations need to process and store. Big data is generated by various sources, and it can be used to gain insights and make predictions in various fields.
What is Business Intelligence?
Business Intelligence (BI) is a set of technologies, applications, and practices used to analyze and report on business data to support decision-making. It involves the use of data, statistical models, and visualizations to gain insights and make data-driven decisions.
What is Change Data Capture (CDC)?
Change Data Capture (CDC) is a method of capturing and tracking changes made to a database over time. It involves tracking and recording changes to data as they occur, rather than periodically taking a snapshot of the entire data set.
What is Cloud Data Storage?
Cloud data storage refers to the practice of storing data on remote servers hosted on the cloud, allowing for scalable, flexible, and cost-effective storage solutions.
What is Contextualized Data?
Contextualized Data is information that has been enriched with relevant context, such as time, location, or other situational factors, making it more meaningful and actionable. Raw data, when viewed in isolation, may not provide clear insights, but when paired with contextual information, it can reveal trends, correlations, and patterns that are crucial for decision-making.
What is Data Enrichment?
Data enrichment is the process of adding additional information to raw data, often from external sources, to make it more valuable for analysis and decision-making.
What is Data Fabric?
A data fabric is an integrated architecture that simplifies and unifies the management of data across hybrid and multi-cloud environments. It provides a seamless, flexible data layer to enable data access and management at scale.
What is Data Governance?
Data governance refers to the management and control of data across its lifecycle. It includes the policies, procedures, and standards that ensure data is accurate, accessible, secure, and used responsibly within an organization.
What is Data Integration?
Data integration refers to combining data from different sources into a unified view. This process often involves merging data from databases, APIs, and various systems to provide a comprehensive dataset for analysis or reporting.
What is Data Lineage?
Data lineage is the tracking of the flow and transformation of data as it moves through various systems, processes, and stages. It provides a visual representation of data movement, making it easier to understand data flows and identify sources of errors.
What is Deep Learning?
Deep learning is a subset of machine learning that uses neural networks with many layers (deep neural networks) to model complex patterns and representations in large datasets.
What is Data Mining?
Data mining is the process of discovering patterns, trends, and insights in large sets of data. It is a technique used to extract useful information from large amounts of data and transform it into an understandable structure for further use. Data mining is commonly used in fields such as marketing, finance, healthcare, and fraud detection.
What is Data Observability?
Data Observability refers to the ability to monitor, measure, and understand the health, quality, and performance of data throughout its lifecycle. It involves tracking key metrics such as data accuracy, completeness, timeliness, and consistency to ensure that data is trustworthy and usable.
What is DataOps?
DataOps is a set of practices, processes, and technologies that aim to improve the speed, quality, and collaboration in data management and analytics workflows. Similar to DevOps in software development, DataOps focuses on automating and streamlining data pipelines to enable faster, more efficient delivery of accurate, high-quality data across an organization.
What is a Data Pipeline?
A data pipeline is a set of processes used to gather, process, and transport data from one system to another. It can be used for ETL or ELT processes and helps ensure data is clean, organized, and ready for analysis.
What is Data Privacy?
Data privacy refers to the handling of personal data in a way that complies with laws and regulations, ensuring individuals' rights are respected regarding the collection, storage, and use of their data.
What is Data Quality?
Data quality refers to the accuracy, completeness, consistency, and reliability of data. It is critical for ensuring that analytics and decision-making are based on trustworthy information.
What is Data Orchestration?
Data orchestration involves coordinating and automating data workflows across different systems and platforms.
What is Data Scalability?
Data scalability refers to the ability of a data system or architecture to handle increasing volumes of data over time, ensuring performance and efficiency as data grows. It is a critical consideration for businesses managing large datasets.
What is Data Security?
Data security involves protecting data from unauthorized access, breaches, loss, or corruption. It includes the implementation of encryption, access controls, and other measures to safeguard sensitive information.
What is Data Sourcing?
Data sourcing refers to the process of identifying, acquiring, and collecting data from various sources to build datasets for analysis or reporting. It may involve sourcing data from internal systems, third-party providers, or publicly available datasets.
What is Data Stream Management?
Data stream management involves the collection, processing, and analysis of real-time data streams. It is particularly relevant for industries like IoT, where continuous data flows from devices and sensors need to be processed and acted upon quickly.
What is Data Transformation?
Data transformation refers to the process of converting raw data into a structured format that is more useful for analysis. It can involve cleaning, normalization, or aggregating data to make it suitable for business intelligence tools or machine learning models.
What is Data Virtualization?
Data virtualization is a technology that allows data from disparate sources to be accessed and queried without needing to move it to a central location.
What is Edge Analytics?
Edge analytics is a method of performing data analysis and processing at the source of the data, rather than in a centralized location such as a data center or cloud. In this way, edge analytics allows for real-time analysis of data as it is generated, without the need to transmit large amounts of data over a network to a centralized location for processing.
What is ELT
ELT stands for Extract, Load, Transform. It is a variation of the traditional ETL process, where the data is first loaded into the destination system, and then transformed and cleaned. The main difference between ETL and ELT is the order of operations. The benefits of using ELT are that it allows for more flexible and efficient data processing.
What is an API?
An API, or Application Programming Interface, is a set of rules and protocols that allows different software applications to communicate with each other. API's allow different systems to share data and functionality, making it possible for different software applications to work together seamlessly.
What is ETL
ETL stands for Extract, Transform, Load. It is a process used to move data from one or more sources into a destination system, such as a data warehouse or a data lake. ETL is a process that helps organizations to collect, integrate, and manage large and complex data sets from multiple sources.
What is Event Processing?
Event processing refers to the real-time analysis and processing of events, which are defined as significant occurrences or changes in a system or environment. Event processing systems typically use complex algorithms and machine learning techniques to analyze and process data in real-time, and can be used for a wide range of applications.
What is Stream Analytics?
Stream analytics is the process of analyzing and gaining insights from data streams in real-time. It is a subset of stream processing and refers to the specific techniques and algorithms used to analyze and extract insights from the data streams as they are generated.
What is Federated Learning?
Federated learning is a machine learning technique that allows models to be trained across multiple decentralized devices or servers without sharing raw data. It helps preserve privacy and reduces the need for data to be centralized.
What is Hybrid Integration Platform?
A hybrid integration platform (HIP) is an integration platform that allows organizations to connect and integrate their on-premises systems and applications with cloud-based systems and applications. It is a combination of both traditional integration technologies and cloud-native integration technologies that can be deployed on-premises, in the cloud, or in a hybrid environment.
What is Industrial DataOps?
Industrial DataOps is the application of DataOps principles to the industrial sector, focusing on the management, integration, and optimization of data from industrial environments like manufacturing, energy, and logistics.
What is In-memory Computing?
In-memory computing is a technology that allows data to be processed and analyzed directly in a computer's memory, rather than being stored on disk. It is a way to speed up the processing of large amounts of data by keeping the data in the computer's random access memory (RAM) instead of reading it from disk.
What is iPaaS?
iPaaS stands for Integration Platform as a Service. It is a cloud-based platform that provides a set of tools and services to help organizations integrate their applications, data, and systems. iPaaS allows organizations to connect and integrate different systems, applications, and data sources in a secure and managed environment, without the need for complex and expensive infrastructure.
What is LLM?
A Large Language Model (LLM) is a type of artificial intelligence model that uses deep learning techniques to understand human-like text, code and images. Trained on vast amounts of data, LLMs can process, interpret, and respond to natural language queries, making them highly effective in tasks like text/code/image generation, translation, summarization, and even conversation.
What is Natural Language Processing (NLP)?
NLP is a field of AI that focuses on the interaction between computers and human language. It involves tasks like language translation, sentiment analysis, chatbots, and speech recognition.
What is NoSQL?
NoSQL (Not only SQL) is a type of database management system that is used to store and retrieve large amounts of unstructured and semi-structured data. It is designed to handle the scale and complexity of modern big data.
What is Predictive Analytics?
Predictive analytics involves using historical data, statistical algorithms, and machine learning techniques to predict future outcomes.
What is Python?
Python is a high-level, interpreted programming language that is widely used in various fields such as web development, scientific computing, data analysis, and artificial intelligence. It is known for its simple and easy-to-learn syntax, which makes it a popular choice for beginners and experienced programmers alike.
What is Real-time Systems?
Real-time refers to a system or process that operates in real-time, meaning it processes and responds to incoming data or events immediately or with minimal delay. Real-time systems are designed to handle and process data as it is generated, without any significant delay.
What is Reverse ETL?
Reverse ETL (Extract, Transform, Load) is a process that involves taking data from a target system and loading it into a source system. It is the opposite of traditional ETL, which involves extracting data from a source system, transforming it, and loading it into a target system.
What is Serverless Computing?
Serverless computing is a cloud-computing model where the cloud provider automatically manages the infrastructure, allowing developers to focus on code without worrying about server management. It is commonly used for event-driven architectures.
What is SQL?
SQL (Structured Query Language) is a programming language that is used to manage and manipulate relational databases. It is used to insert, update, delete and retrieve data from a relational database. It is a standard language used by most relational databases, such as MySQL, Oracle, Microsoft SQL Server, and others.
What is Stream Processing?
Stream processing is a method of processing data in real-time as it is generated, rather than in batches. In this way, stream processing allows for real-time analysis of data as it is generated, rather than having to wait for the data to be collected and stored before it can be analyzed.
What is Structured Data?
Structured data refers to data that is organized in a specific format or schema, such as rows and columns in a table. It is well-defined and follows a specific structure, making it easy to search, query, and analyze. Structured data can be stored in various forms such as relational databases, spreadsheets, and CSV files.
What is Transformed Data?
Transformed Data is data that has undergone various processing steps to change its format, structure, or content, making it suitable for specific use cases or analysis. During the transformation process, raw data is cleaned, enriched, aggregated, or otherwise modified to align with business needs.
What is Unified Namespace?
A Unified Namespace (UNS) is a single, consistent data structure or layer that integrates and organizes data from multiple sources in a way that makes it easy to access and manage. Big data is generated by various sources, and it can be used to gain insights and make predictions in various fields.
What is Unstructured Data?
Unstructured data refers to data that does not have a specific format or schema, such as text, images, audio, and video. It is not organized in a specific way and is often unformatted or semi-formatted, making it difficult to search, query, and analyze. Unstructured data can be stored in various forms such as text files, images, audio and video files, and social media posts.
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