How much cloud data management does any single instance or any single organisation’s IT stack actually need?
Don’t try and answer that, it’s a trick question.
The answer is obviously impossible to assess i.e. the discombobulated nature of cloud connectivity, complexity and coalescence demands and almost infinite variety of cloud management layers, tiers, toolsets and architectural intelligence trickery.
Aiming to connect some of the otherwise disparate islands of functionality that exist out there this month is enterprise cloud data management company Informatica with tighter integrations in its Intelligent Data Management Cloud to Snowflake.
Self-styling itself as the ‘data cloud for dummies’ company, this new synaptic connection to Snowflake will advance Extract, Load and Transform (ELT) capabilities and offer native support for Snowflake’s Java User Defined Functions (UDF) to enterprise customers.
Informatica claims this is a key boost for large enterprises who want to move their data to Snowflake through its Intelligent Data Management Cloud and give data scientists and developers the chance to scale analytics and cloud applications.
Tarik Dweik, head of technology alliances at Snowflake says that customers will have the ability to load data from nearly anywhere.
As data proliferation and fragmentation grows, this announcement resonates with the fact that technologists are focused on advanced ELT use-cases where cloud-native mass ingestion is needed to rapidly load and synchronise data from applications.
In the case here, that could be applications, tools and platforms such as SAP, Salesforce, NetSuite, Zendesk, Microsoft Dynamics 365, Workday, Marketo, ServiceNow and Google Analytics… with the data moving into Snowflake via an enterprise-grade, easy-to-use, wizard-driven application synchronisation service to drive new analytics and applications built on Snowflake.
According to Rik Tamm-Daniels, Informatica’s VP for strategic ecosystems and technology, with Informatica’s new Intelligent Data Management Cloud platform, customers can seamlessly transform, cleanse and govern this application data into Snowflake without any hand-coding or having to assemble an end-to-end solution from disparate systems.
Talend also on the freeze to Snowflake
In related news, data integration and integrity company Talend said it is working closely with Snowflake to offer an instant way for users to verify the quality of their data inside Data Cloud.
Talend Trust Score for Snowflake uses Snowpark to assess and improve data accuracy inside a Snowflake environment and so provide quality data.
Leveraging Snowflake’s Snowpark developer environment and Java UDFs, Talend Trust Score for Snowflake with Snowflake makes it possible for customers to use sophisticated data profiling algorithms directly to perform reliability checks on their Snowflake data. With a click, Snowflake customers will be able to increase their performance and accuracy by running quality checks on entire data sets without the use of external applications or moving sample sets.