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Launching an Inner Knowledge Market with Atlan
The Lively Metadata Pioneers sequence options Atlan prospects who’ve lately accomplished an intensive analysis of the Lively Metadata Administration market. Paying ahead what you’ve realized to the subsequent knowledge chief is the true spirit of the Atlan neighborhood! So, they’re right here to share their hard-earned perspective on an evolving market, what makes up their fashionable knowledge stack, progressive use instances for metadata, and extra.
On this installment of the sequence, we meet Cristina Perez Martinez, Knowledge Engineer and Architect, and Ezequiel Barbero, Market & Enterprise Intelligence Supervisor at Telefónica Tech, who share how a contemporary knowledge cataloging expertise and column-level lineage will help a broad imaginative and prescient for knowledge democratization.
This interview has been edited for brevity and readability.
Might you inform us a bit about your self, your background, and what drew you to Knowledge & Analytics?
Ezequiel Barbero:
I’ve acquired a Masters in Massive Knowledge and have labored in Knowledge & Analytics since 2002. I began at Telefónica in Argentina with the BI Knowledge Workforce engaged on ETLs based mostly in SQL. Then I labored in Knowledge Engineering serving to with Knowledge Science, working with the top of that workforce in Argentina.
In 2019, I got here to Spain to work with their Knowledge Science workforce on Advertising and marketing Intelligence, and in 2021 I joined Telefónica Tech to begin the BI Workforce.
Cristina Perez Martinez:
I began working at Telefónica in 2019 as a Python developer, and I moved to Telefónica Tech in 2021. My workforce has primarily been working as Knowledge Engineers and Knowledge Architects for the BI workforce.
Would you thoughts describing Telefónica, and the way your knowledge workforce helps the group?
Cristina:
Telefónica is split into fairly a couple of completely different corporations, however as an entire, it’s a Telecommunications Enterprise. Right here, in Telefónica Tech, the digital enterprise unit, we’ve been centered on digital applied sciences akin to AI & BD, connectivity and IoT, Cybersecurity, Cloud, and Blockchain.
Our workforce is split into two, with a part of the workforce centered on structure and engineering, getting uncooked knowledge, then standardizing and remodeling it till it goes into Snowflake, our Knowledge Warehouse. The remainder of the workforce is targeted on Knowledge Evaluation, based mostly in Snowflake and coding in SQL. From there, they develop dashboards in PowerBI.
Ezequiel:
Telefónica Tech has a workforce engaged on IoT and Massive Knowledge for exterior use instances, however our workforce is accountable for inner use instances, supporting the corporate. We help infrastructure, transformation, and for nearly a 12 months now, Knowledge Governance.
What does your knowledge stack seem like?
Ezequiel:
Our stack is predicated on Microsoft Azure, and we use Knowledge Manufacturing facility for Orchestration. We use Databricks’ ETL software, blob storage, and knowledge lake. Snowflake is Telefónica’s knowledge warehouse.
Why seek for an Lively Metadata Administration answer? What was lacking?
Ezequiel:
Our firm has over 6,200 folks, however our workforce is small relative to the whole group. So if it’s necessary to enhance knowledge democratization, then that wouldn’t be attainable with out self-service, and with out Knowledge Governance.
Why was Atlan match? Did something stand out throughout your analysis course of?
Ezequiel:
We had been first in search of a cloud-based SaaS answer that was simple to deploy and straightforward to arrange.
Cristina:
Our purpose was to have a spot the place we might create a catalog of knowledge that was accessible sufficient to the remainder of the corporate. It was additionally necessary to grasp the lineage between Snowflake and PowerBI. Our main purpose was to grasp the influence that modifying a supply would have on our knowledge warehouse, so column-level lineage ensures end-to-end visibility and traceability. Moreover, we acknowledge the necessity for a sturdy software to strengthen safety of our knowledge platform, permitting us to assign roles and permissions to make sure that solely licensed folks have entry to particular info, in addition to the power to carry out audits which is crucial to take care of the integrity and compliance of our knowledge operations.
What do you plan on creating with Atlan? Do you may have an concept of what use instances you’ll construct, and the worth you’ll drive?
Cristina:
One of many necessities we had is to create considerably of a market for our knowledge, with all the things based mostly on Atlan belongings, and we’re engaged on launching that to start with of this 12 months. From there, we’re wanting ahead to populating much more metadata in Atlan and Snowflake.
Sooner or later, we’re enthusiastic about the potential of utilizing Atlan AI. Our purpose is to make accessing knowledge even simpler for folks, and with the ability to chat with Atlan about knowledge would make it simple for folks to seek out what they want.
Picture by Mario Caruso on Unsplash
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