From Chaos to Confidence: How Mistertemp Optimized their Trendy Information Stack with Atlan – Atlan


Recruitment and Short-term Work Placements Chief Makes use of Automated Lineage to Deprecate Two-thirds of Information Warehouse Belongings

At a Look

  • Mistertemp, a pacesetter in recruitment and momentary work primarily based in France, sought to enhance the navigability and value of their newly carried out fashionable information stack (Snowflake, Fivetran, Looker, Airflow, and dbt).
  • By adopting Atlan, Mistertemp’s information crew may use automated column-level lineage and recognition metrics to find out which of their information belongings had been used or could possibly be deprecated.
  • In consequence, Mistertemp was capable of deprecate half of their Snowflake tables, representing two-thirds of their information belongings, and over 60% of their Looker belongings.

The large distinction now’s that we’re assured as a crew after we’re speaking a couple of information asset.”

Based mostly in France, Mistertemp is a market chief in momentary work placements, servicing over 12,000 shoppers and 55,000 staff in 2022. As a dealer between firms searching for expertise and folks searching for alternative, information performs a key function in Mistertemp’s aim to align these events as successfully as potential.

Driving that dedication to information is David Milosevic, who joined Mistertemp as Head of Information & Analytics in 2019. “My preliminary aim was to assist discover the appropriate instruments, group, and options to assist everybody within the firm have a greater understanding of information,” David shared.

Even after rising into a pacesetter in its area, Mistertemp’s management refuses to be complacent. Amid the expansion of distant work, modifications in worker expectations, and the evolving wants of firms searching for nice expertise; the stability between Mistertemp, the businesses they service, and the candidates they place is altering.

David defined information’s function on this transformation: “Our aim is to see how we will optimize all of the exchanges we’ve got with these totally different events — sharing data from our must job boards, for instance, or getting functions for these advertisements that we placed on job boards. How can we optimize the data we get in order that they are often matched with the wants of shoppers and vice versa?”

To navigate their altering market, it’s essential that Mistertemp successfully use its information, and David’s crew has been accountable for constructing options, adopting instruments, and creating processes to help that journey. David encourages his crew to take a proactive function in how Mistertemp makes use of its information, explaining, “Apart from KPIs that you could placed on our groups’ efforts, we try to go to the following step, which is to include information into our processes to enhance every of them.”

Mistertemp’s Trendy Information Stack: Atlan + Snowflake, Fivetran, Looker, Airflow, and dbt

“In my space, we’re principally specializing in what we name the Trendy Information Stack,” David shared. Initially deciding on Fivetran to ingest information, Mistertemp’s foundational decisions for his or her stack included Snowflake as their information warehouse and Looker as their BI layer. Added later had been Airflow and dbt.

Regardless of adopting best-in-breed instruments to help their transformation, Mistertemp’s management felt {that a} piece was lacking. “I’ve to present credit score to our CTO [Francois-Emmanuel Piacentini]. His mindset was that till we’ve got a option to not simply doc, however tag, establish, and shortly seek for belongings, we aren’t the house owners of our information,” David shared. “This actually resonated with our crew. For a very long time, we couldn’t put our finger on what was lacking.”

Mistertemp wanted a governance and collaboration layer, built-in to and able to navigating their more and more complicated information stack. “We wanted so as to add one thing to the equation to be sure that as soon as a necessity appeared (being a product want, a advertising want, a monetary want, a necessity from a shopper) that we may confidently say, okay, it was carried out up to now or not,” David defined.

With out this layer in place, David’s crew was accountable for scouring their information property, layer by layer, every time a query about their information belongings was posed. The hassle to find out what belongings existed, not to mention the character of these belongings or the efficacy of the information, was important. “Answering these questions took us quite a lot of time,” David mentioned. “Eradicating this from the equation, and having all the pieces laid out and queryable was actually vital if we needed to step up and implement all these future use instances.”

Mistertemp’s CTO successfully communicated his imaginative and prescient for a way their information perform would want to alter. It was on David and his crew to get it carried out.

Atlan Arrives

After a radical seek for an energetic metadata administration platform, Mistertemp selected Atlan. “As quickly as we acquired our arms on Atlan, step one was to attach all our instruments in our stack in order that we had an enormous image of all the pieces in our space of labor”, David shared. He shortly built-in Fivetran, Snowflake, dbt, and Looker with Atlan, in addition to upstream methods like Salesforce and Postgres databases, providing a transparent image of Mistertemp’s information ecosystem.

“We needed to have as a lot visibility as we may, and that was very simple. We solely wanted a pair days to set it up and ensure we had been glad,” David added. “This was very easy and we had been very glad to immediately see all our belongings out there and queryable. We may simply kind ‘contract’ and discover all tables or columns or studies that seek advice from that there.”

With a fast win in-hand, and visibility into how information moved by way of their stack, David’s crew was able to put this newfound functionality into apply. “Step one was very easy and really rewarding. However that was not only for the enjoyable of it,” David defined, alluding to far larger ambitions with Atlan.

Utilizing Atlan to Resolve Effectively-intended Technical Debt

Atlan’s introduction into the Mistertemp ecosystem gave David the attitude and functionality essential to simplify their complicated technical panorama.

Whereas pleased with their fashionable information stack, Mistertemp’s information crew struggled with navigability and manageability previous to Atlan’s arrival. “A giant aim we had, and wish to proceed to pursue, is that we wish to guarantee what we’ve got in Snowflake or Looker are solely information or studies which are helpful,” David defined. “It’s really easy with fashionable information stack instruments to principally join all the pieces you’ve and seize the information.”

Excited by the prospect of higher servicing their enterprise companions, and with enterprise companions enthusiastic about freely out there information, David’s crew had spent earlier years connecting quite a few downstream methods and constructing quite a few studies for one-off questions. “Again three years in the past, the aim was to have all the information related,” David shared.

At any time when a brand new information supply was requested, David’s crew as soon as discovered it best to go to Fivetran and hook up with the supply system to disclose the out there tables. Moderately than diving into these methods to decide on solely related information, it was easier and quicker to recreate the information in Snowflake instantly, consuming what was related downstream.

“With instruments like Fivetran, it’s very simple so as to add new connectors,” David mentioned. And over time, selections to attach and ingest information for every request multiplied right into a increasingly more complicated information property. A request from Mistertemp’s growth crew meant that every one Jira belongings had been synchronized, and a request from the help crew led to synchronizing each Zendesk ticket. “Why not synchronize all the information instantly? Possibly we’ll have some dashboards in place down the street,” David elaborated about their mindset on the time. 

Mistertemp’s information crew had been exceeding enterprise wants and had been well-intended. However with out an energetic metadata administration platform lending visibility into the implications of synchronizing a excessive quantity of information, they had been constructing technical debt, with a ballooning Snowflake footprint and quite a few unused however supported Looker studies. 

All these fast selections created quite a lot of belongings in Snowflake that principally and not using a enterprise use had been by no means actually touched or by no means actually documented or by no means actually related to our BI software or another software. So they simply stayed there being synchronized, costing us cash.

“It was very simple to create studies to showcase information as one-shots, however that creates quite a lot of debt, and quite a lot of overhead on our crew. Our crew is just 4 individuals,” David shared. “We needed to say in some unspecified time in the future no matter is related and synchronized from Fivetran to Snowflake ought to be the minimal viable information. We needed to verify something that we seize was related downstream to a use case or report that’s utilized by an finish person.”

The place end-to-end visibility was as soon as elusive, Atlan supplied close to instantaneous understanding of the work forward, and David’s crew had been prepared to repair Mistertemp’s long-simmering information property complexity, as soon as and for all.

Deprecating Two-thirds of Their Belongings with Automated Column-level Lineage

Utilizing Atlan’s automated lineage, David’s crew started working analyzing Fivetran and Snowflake, filtering belongings by whether or not or not they’d lineage, and shortly and simply figuring out which belongings had been, or weren’t, related downstream. And with Atlan Recognition, a characteristic that exhibits customers the frequency of utilization and queries in opposition to an information asset, they may decide how typically individuals used these belongings, if in any respect.

For the primary time, David’s crew had been capable of perceive the dimensions of what they’d been sustaining. Of their 1,500 tables and 30,000 belongings on Snowflake, fewer than half of the tables and one-third of the belongings had been used within the previous 12 months. “After the cleanup, it went right down to just a little bit lower than 600 [tables]. Greater than half our belongings had been cleaned up,” David shared.

All the pieces downstream modified. We had been capable of see each present connection in Fivetran. We may see what was really used. We saved these, and for all the pieces else, we might disconnect.”

Atlan’s column-level lineage and utilization metrics additionally revealed that constructing one-off studies had additionally exacted a price. Mistertemp’s BI layer had ample alternative for cleanup, with 60% of their belongings like dashboards, views, dimensions, and measures going unused. 

I believe 60%, perhaps 70% of Looker dashboards weren’t actively used and had been creating quite a lot of overhead on the information analysts,” David mentioned. Mistertemp’s analysts had been sustaining these unused studies as underlying belongings advanced or methods modified upstream, driving distraction and pointless effort.

Rising Context and Optimizing Information Processes, Now Accessible in File Time

Even after deprecating as many as two-thirds of their belongings, David continued to push his crew to search out extra alternatives to optimize their information property.

With the data that what remained in Snowflake was helpful to their enterprise companions, Mistertemp’s information crew started the method of correctly tagging and documenting the remaining belongings. “Earlier than final 12 months, earlier than we began pondering of utilizing Atlan or different instruments, we considered utilizing Snowflake or Looker,” shared David. However with Atlan, asset documentation is accessible to colleagues who don’t use Snowflake or Looker, laying the groundwork for a single level of context for Mistertemp’s enterprise information, accessible to all.

With a transparent thought of how typically belongings are used, Mistertemp’s information crew now optimizes how typically information is synchronized, saving computing prices by selecting an acceptable cadence (month-to-month fairly than hourly, for example) that matches enterprise wants. And with their newfound visibility into their Looker panorama, they may merge related studies to cut back Mistertemp’s BI footprint and enhance maintainability.

And eventually, by figuring out the recognition of their information belongings, then deprecating them previous to tagging and defining phrases, Mistertemp prevented unnecessarily including context to tons of of tables and belongings. “That may not be the configuration for each firm, however we’ve got quite a lot of clients and solely 4 individuals attempting to catch up,” mentioned David. “We wanted to search out an environment friendly means to assist us scale, and never linearly.”

Making a Clear Information Property with Atlan

Months after cleansing up their information property with Atlan’s automated lineage and utilization metrics, Mistertemp’s information crew continues to reap the advantages. 

The large distinction now’s that we’re assured as a crew after we’re speaking a couple of information asset.”

When requested a couple of information asset, David’s crew can now, at a look, decide whether or not or not it’s getting used, the place it’s getting used, and the way steadily it’s getting used and synchronized. If belongings or studies exist already, their enterprise companions shortly get what they should make extra data-driven selections. And if one thing new must be created, the information crew can extra shortly reply with an answer strategy that features the appropriate information sources, the appropriate documentation, and the appropriate visualization.

“All of that’s principally solely in a single place,” mentioned David. “Earlier than, it was a dialogue we needed to have with a number of individuals within the crew. We wanted to determine principally from one software to a different software. We went from being just a little bit chaotic to just a little bit extra streamlined, and anybody within the crew is ready to reply questions.”

No matter the place information lived or what type it took, Atlan grew to become Mistertemp’s first step to resolving enterprise wants. “We all know as soon as we’ve got written this down, anybody that has a query can discover the reply no matter their layer,” David shared. “I’ll emphasize how a lot time this will save us, simply lowering these discussions and ensuring we spend extra time on motion.”

And with this better focus, and time saved, David’s crew is taking a extra proactive function in enhancing the Mistertemp enterprise. Most not too long ago, they contributed to a mission to enhance Value per Hiring, a key enterprise metric. 

“I believe it’s a type of subjects we’ve got needed to resolve for so long as I’ve been right here, for greater than three years. We acquired uninterested in not with the ability to establish the issues we would have liked to shift or resolve or put collectively,” David defined. “I believe with the assistance of Atlan, we had been capable of settle every of these arguments one after the other by both having the correct definition put into the glossary, or by having the appropriate lineage displayed in entrance of us so that everybody talks the identical language. It’s a mixture of instruments we didn’t have earlier than that helped us crack that equation that we had been prepared to do, however by no means discovered time, power, or instruments to resolve.”

A Extra Assured Information Crew

Reflecting on his and his crew’s journey, David continues to return to the identical feeling: confidence.

Mistertemp’s information crew is reworking into a real enterprise enabler, proactive of their strategy to sustaining their information property, and on the prepared with the solutions and options their enterprise companions want. “It’s no extra a query of ‘ought to we’. It’s extra like ‘how can we?,” David shared. “Folks depend on us just a little bit extra now that we will precisely give them solutions to their questions, perhaps not instantaneously, however in a short time.”

“We’re simply in the beginning of our journey with Atlan,” David concluded. “Whether or not you’re a product proprietor, a developer, a monetary particular person, a advertising particular person, we simply wish to be sure that everybody finds a means to enhance their every day routine. It’s not solely cleansing up for the information crew to be assured, but it surely’s the primary stone to ensure that everybody to have the ability to construct on prime of that.

Photograph by Alex Kotliarskyi on Unsplash

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