Attunity offers solutions for creating analytics-ready data sets on the Databricks’ Unified Analytics Platform. They are designed to automate streaming data pipelines to make data seamlessly available to accelerate machine learning (ML), artificial intelligence (AI) and data science initiatives. Watch this on demand webinar to learn from the experts at Databricks and Attunity to learn how your organization can benefit.
In this webinar, you will see how world-leading provider of mobile modular power, temperature control and energy services Aggreko, have designed an effective technology stack in Azure to enable them to accelerate the delivery of value using Microsoft & Attunity products. How to drive business value from data to support business strategy Designing an effective data architecture to support insight-driven decision making Assessing and utilising the right technologies in the cloud to accelerate delivery of value Considerations, challenges and lessons learned along our data journey.
Attunity and Microsoft have a solution to help data-driven organizations get more value from data. This live webinar will explain how to: - Implement a fully managed cloud data warehouse for enterprises, combining fast query performance with industry-leading data security - Raise the bar on cloud data warehouse price-performance per industry analyst GigaOm - Integrate real-time data to ADW with the industry's broadest range of sources using change data capture (CDC) technology - Automatically generate ETL code to help data architects rapidly configure and manage ADW.
Express Scripts is reimagining its data architecture to bring best-in-class user experience and provide the foundation of next-generation applications. The challenge lies in the ability to efficiently and cost-effectively access the ever-increasing amount of data. This online talk showcases how Apache Kafka® plays a key role within Express Scripts? transformation from mainframe to a microservices-based ecosystem, ensuring data integrity between two worlds. It will discuss how Attunity's change data capture (CDC) technology is leveraged to stream data changes to Confluent Platform, allowing a low-latency data pipeline to be built.
In this webinar, we will examine the five key steps to be successful with DataOps, including the process and cultural shift required. We will also discuss the results of enabling DataOps success, such as improved productivity, streamlined and automated processes, increased output and higher collaboration across teams. CDOs, Data Architects, Data Engineers & Analytics Teams Should Attend to Learn How to: · Better manage data flow across the data lifecycle ? from ingestion to provisioning to analytics · Derive tips from use cases involving data lakes, cloud and data warehousing for better business insights · Increase collaboration, productivity and business value · Leverage new technology and approaches to enable data pipeline automation.
Apache NiFi is an easy to use, powerful, and reliable system to process and distribute data. It provides an end-to-end platform that can collect, curate, analyze, and act on data in real-time, on-premises, or in the cloud with a drag-and-drop visual interface. It?s being used across industries on large amounts of data that had stored in isolation which made collaboration and analysis difficult. Join industry experts from Hortonworks and Attunity as they explain how Apache NiFi and streaming CDC technology provides a distributed, resilient platform for unlocking the value of data in new ways. During this webinar, you will: Discover the advantages of Apache NiFi See how to create a NiFi dataflow Learn how industries like yours are using NiFi Accelerate data replication.
Market leaders in every industry are beginning to see the power of real-time big data integration and how connecting it can enable them to re-imagine their markets, customers, products, and business models. Christian Nicoll, Director of Platform Engineering & Operations at Generali Switzerland guides us through their journey of setting up an event-driven architecture to support their digital transformation project.
On-premises and cloud data lakes are popular for enabling analytics, big data storage, self-service data practices, and warehouse modernization. However, data management challenges can often make finding value extremely difficult. In fact, when data lakes first entered the market, many organizations simply dumped data into the lake, transforming them into entities more akin to swamps that were nearly impossible to leverage, navigate, or trust. The uncontrolled and undocumented swamp was the first generation of a data lake that had many failings, but it also provided numerous learning opportunities. Second generation data lakes have better internal organization, are typically governed better, and make use of modern ingestion technologies that support all forms of data and metadata integration. In addition, they leverage automated data pipelines as a best practice. . You will learn: - The evolution and necessity of the modern data lake - Options for efficient, real-time data ingestion at scale - The importance of data pipeline automation.
Modernising Data Architecture With Streaming CDC Expanding analytics requirements have increased the appetite for massive data volumes. However, these data flows can create bottlenecks, preventing timely and modern analytics innovations such as machine learning. This is where streaming Change Data Capture (CDC) comes in. By using CDC to power next-generation streaming environments, we can reconfigure data architectures to enable efficient, scalable and real-time data integration that protects production workloads. In this webinar, we discuss the market need for streaming CDC, how it differs from other techniques, and use cases and case studies.
Fanatics, a popular sports apparel website and fan gear merchandiser, needed to ingest terabytes of data from multiple historical and streaming sources – transactional, e-commerce, and back-office systems – to a data lake on Amazon S3.
This webinar featured experts from Attunity, MapR and Publishers Clearing House, as they explain their process of moving large volumes of data on a DB2 mainframe environment to Hadoop to perform large-scale analytics.
Read the data sheet, Attunity Enterprise Manager – Your Command Center for Large Scale Data Integration.