Informatica is boasting a total of 25 new features across its suite of data management technologies which could all be grouped under the phrase “we can automate that!” The company – which names the US Airforce, Axa insurance and BMW among its customers – introduced its AI and machine learning technology for data management, dubbed
Informatica is boasting a total of 25 new features across its suite of data management technologies which could all be grouped under the phrase “we can automate that!”
The company – which names the US Airforce, Axa insurance and BMW among its customers – introduced its AI and machine learning technology for data management, dubbed Claire, in 2017. The latest slew of features aims to expand on its application. They fall into broad categories of cloud data management, mobile device management (MDM), integration platform as a service (iPaaS to some), data governance and data catalogues.
For fear of sending Register readers into a deep slumber, let’s stick to the highlights under each banner.
In the cloud, Informatica supports serverless architecture – where all the knobs and buttons of virtual servers are discarded and only the services necessary to support the application are provided. Users, meanwhile, only pay for what they use, rather than the capacity of a nominal server.
Within this environment, Informatica is touting engineering pipeline recommendations, cross-data pipeline categorisation based on similarity, streaming data lineage, and data prep recipe recommendations based on its Claire machine learning-powered recommendation engine.
Tony Baer, an analyst with dbInsight, said it would help rationalise the mess of user-generated data pipelines.
“As low code/no code tools make it almost too easy to build pipelines, customers can easily build up a bewildering array of one-offs. Informatica’s new tool introspects the pipelines, scanning data sources, operations, and targets to identify which pipelines use similar transformation patterns, and guides users on building configurable templates that reduce proliferation and makes them more configurable and maintainable.”
MDM has always been labour intensive, but Informatica hopes to ease the pain. This includes recommendations, through natural language processing (NLP), of how data might fit into a master data schema and graph database power descriptions, and analysis of relationships within master data.
The Informatica iPaas supports multi-cloud and hybrid cloud architecture across technologies, systems and applications, as well as enhanced Azure and AWS support.
An automated data marketplace is next on the list. The idea is, according to the firm, that data engineers can specify general options available for provisioning data to consumers, the methods, formats, locations, cadences for data delivery, and the security constraints to accessing these options, without having to go into all the fine detail themselves.
Lastly, there is a new data catalogue, a concept that is supposed to reveal data provenance, such as who created the data and what it has been used for. This includes metadata scanners for analytics applications like SAP BW and SAP BW/4HANA, streaming platforms like Apache Kafka, NoSQL databases like MongoDB, BI tools like Qlik Sense, and multi-vendor ETL tools.
The point of all this is that organisations are finally waking up to the fact that their success may relate to how they collect, analyse and act on data. Automating the machinery behind that is Informatica’s mission. If only its audience could stay awake long enough to hear it. ®