Informatica’s Data Management Cloud gets new data engineering, MLOps tools:

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Enterprise data management vendor Informatica has updated its Intelligent Data Management Cloud (IDMC) with new tools and applications to help ease data management and engineering tasks which, the company said, are posing a particular challenge the face of talent shortages and economic uncertainty driven by the tailwinds of the pandemic.

The updates, announced at the company Informatica World conference Tuesday, include: InfaCore; ModelServe; a self-service iPaaS (integration platform as a service); and applications that are part of the company SaaS 360 product range. The new applications and capabilities are expected to maximize efficiency in handling complex challenges such as data management, integration and engineering, the company said.

Separately, in the wake of launching a focused data management platform for retail customers in March, Informatica also announced the release of two more industry-tailored versions of IDMC – one for financial services, and the other for health and life sciences.

Informatica aims to speed data engineering:

In order to help enterprises deal with the ongoing talent shortage, the company has introduced the InfaCore “plug and play” framework, designed to support data science tasks and application development.

It is meant to simplify the creation of data pipelines by turning voluminous code into a single function, and to accelerate the ability of data scientists and data engineers to consume, transform, and prepare data from any source within their development environment, Informatica said.

The function is also designed to be deployed in applications, leveraging their native UIs and accelerating time to market.

More often than not developers and data scientists, though they are tech-saavy, might not be well-versed in data integration and transformation work, and in such cases a framework like InfaCore can come in handy, said Doug Henschen, principal analyst at Constellation Research.

“The announcement presents a way to invoke data-integration pipelines and components within third-party development and data science environments, sparing these professionals from having to recreate that work,” Henschen said, adding that there are other iPaaS platforms that can help in data integrations by calling APIs.

Operationalizing machine learning models:

Informatica says that a major barrier for enterprises to implement machine learning solutions is the challenge of integrating them with existing infrastructure. In order to help solve this problem, the company is offering a new service, dubbed ModelServe, in private preview.

Using the service, customers can operationalize any machine learning models from within their pipeline with one click, the company said, adding that the MLOps tool offers end-to-end visibility and control of machine learning models for data engineers.

The company also has introduced a machine learning model registry to upload, deploy, and manage machine learning models, and then operationalize those models at scale within data pipelines with Informatica’s serverless infrastructure. This, according to the company, saves time and effort.

While Informatica may be addressing a common model ops challenge that many data science and focused model-ops vendors are also addressing, it is not typical to see a machine learning model registry within an iPaaS environment, Henschen said.

“Machine learning model registries are generally found in model ops and data science environments. But the new tool gives customers (and especially Informatica customers in particular) another option,” Henschen said.

Create your own accelerator via no-code platform:

While IDMC’s data marketplace, launched last year, was aimed at reducing the need – via a sharing model – to code for connectors, APIs, and templates, the company is now also providing a no-code platform within its software suite for developers to create their own connectors in cases where they do not find one.

Other new capabilities include predictive data intelligence and SaaS applications within Informatica’s 360 product line.

While predictive data intelligence will throw up recommendations for maximizing the potential of an enterprise’s data by suggesting actions to be taken for data management and engineering tasks, domain-specific 360 solutions will help implement master data management solutions faster, Informatica said.

Examples of these applications are Supplier 360 SaaS and Product 360 SaaS. Supplier 360 SaaS is an AI-powered application for management of suppliers and contacts, supplier relationships and hierarchies, business rules, and supplier onboarding workflows. Product 360 SaaS, meanwhile, is an application for product data, product relationships and hierarchies, content enrichment and data quality business rules, and governance workflows.

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