Attunity automates streaming data pipelines for AI, ML
Data integration and big data management solutions provider Attunity has released an analytics platform designed to automate streaming data pipelines for AI, ML, and data science initiatives.
According to Attunity, data engineering teams struggle to keep up with demand for real-time data sets for machine learning applications. In addition, data integration and migration can be a manually intensive and complex endeavour; challenging to assemble and often resulting in outdated data when it is finally ready for data scientists.
Attunity says that it assists enterprises in overcoming these challenges with efficient changed data transfer at scale and automation of data transformations in Apache Spark that accelerate data pipelines — data sets in Databricks' Unified Analytics Platform.
Attunity for Databricks Unified Analytics Platform, in combination with Attunity software, is able to provide continuous change data capture, delivery, and automated refinement for creating analytic-ready datasets in the platform.
Databricks' Unified Analytics Platform also makes it easier for enterprises to build data pipelines across various siloed data storage systems. Databricks provides one platform to unify data processing and machine learning initiatives, making AI achievable.
"With this new data pipeline automation offering for the Databricks Unified Analytics Platform, we further expand the agility for organizations that are looking to deploy next-generation analytics in the cloud and deploying DataOps practices," comments Attunity chief marketing officer Itamar Ankorion.
“Our ability to reach into virtually all enterprise systems and deliver real-time, analytics-ready and transactionally consistent data without coding is a powerful enabler for data scientists, allowing them to generate the business insights that accelerate corporate decision making and growth."
Attunity for Databricks Unified Analytics Platform helps enterprises to:
• Accelerate time to value and increase ROI – With Apache Spark as a high-performance data processing engine, Attunity automates the data and delivers analytics-ready data sets into Databricks Unified Analytics Platform. Data engineers can quickly create reusable, automated data pipelines that streamline the delivery of analytics-ready data sets to data scientists and other data consumers, lessening the need for manual coding or expensive development resources.
• Reduce reliance on inefficient data preparation – Attunity provides more agile data pipeline generation that better meet the needs of data scientists who can now spend more time on high-value analysis and less time on preparing data.
• Use real-time time with continuous integration at scale – Attunity's CDC technology provides the efficiency and low-latency needed for massive machine learning data sets in the cloud.
• Deploy in multi-cloud environments for flexibility and agility – Attunity supports Databricks on both Azure and AWS in addition to a wide range of data lake, warehouse and streaming services on these platforms.
• Employ analytics-ready and transactionally consistent data – Attunity provisions full support for Databricks Unified Analytics Platform ACID capabilities and provides the ability to update transactions in the order they are committed on the source systems.