Unifying a Information Stack and Leveraging Self-Serve Analytics with Atlan
The Lively Metadata Pioneers collection options Atlan clients who’ve accomplished a radical analysis of the Lively Metadata Administration market. Paying ahead what you’ve discovered to the subsequent knowledge chief is the true spirit of the Atlan group! So that they’re right here to share their hard-earned perspective on an evolving market, what makes up their trendy knowledge stack, progressive use instances for metadata, and extra.
On this installment of the collection, we meet Daniel Ferguson, Information and Analytics Director at PHMG, an audio branding firm that helps over 36,000 purchasers throughout 56 nations sound their finest. Daniel shares how PHMG reworked their knowledge stack from fragmented to unified, and the way Atlan has been an important piece in by monitoring lineage, managing reviews, and easing workforce onboarding.
This interview has been edited for brevity and readability.
May you inform us a bit about your self, your background, and what drew you to Information & Analytics?
I was a DJ after which labored as a sound engineer constructing recording studios. Throughout my time as a sound engineer, I discovered myself within the technical and analytical facet of issues. After beginning a household, I wished a change. After promoting my recording studio, my mom, who managed a council workplace, supplied me a job and I began out within the name heart unit, dealing with calls. It rapidly turned obvious that I may do extra than simply calls, so I moved to the database workforce.
I began finding out for a level in Economics and Mathematical Science at The Open College whereas working on the council. Utilizing the abilities learnt on my diploma I began to construct logistic regression fashions to focus on contacts within the name heart I had beforehand labored in. I proposed that, with only one individual, I may obtain the identical outcomes as your entire workforce. My work generated 300% extra outcomes than the workforce’s mixed efforts by optimizing knowledge assortment, addressing lacking data, and cherry choosing the perfect contacts. After that I used to be hooked on the facility of knowledge & analytics.
I then constructed an organization offering knowledge providers to different Native Authorities. Close to the tip of my diploma, a consultancy in Scotland, Aquila Insights, supplied me a place. They labored with purchasers like Sony, Workplace Depot, and RBS, which gave me early publicity to the information occupation. From there, I superior within the area and finally joined PHMG. My journey into knowledge was considerably unintentional, nevertheless it introduced me to the place I’m at this time.
Would you thoughts describing PHMG?
We specialise in audio branding. Consider logos like Netflix or Disney Plus, via sound alone, these manufacturers are immediately recognizable as trade leaders in leisure and streaming even when their visible logos should not in sight.
We additionally transcend conventional audio branding by growing customized music tailor-made to every group. We’ll take Atlan for example: What’s Atlan about? What do you symbolize? What’s the kind of rhythm that it desires to convey?
This connection between music and identification is what attracted me to the corporate. Now we have been extremely profitable, working in 56 nations with 36,000 purchasers.
May you describe your knowledge stack, and the way it got here collectively?
Once I obtained right here, we had been utilizing SQL servers with Excel spreadsheets. There have been restricted to no interactive reviews, and each knowledge request needed to be raised to the information workforce.
There was a have to modernize the data flowing into the corporate and implement the proper know-how to attain this effectively and reliably. I targeted on discovering know-how options that will streamline operations and scale back the necessity for extra engineers.
I used to be actually cautious with know-how choice, avoiding options for the sake of it, and never constructing from scratch. Whereas Azure Cloth affords a complete resolution, for instance, it’s nonetheless new and that comes with extra dangers, however is one thing I’m preserving my eye on. It’s essential to decide on the perfect instruments for the job and guarantee they work nicely collectively. Investing in a seamless course of with these instruments permits you to begin robust and exhibit worth rapidly, with room to evolve as you scale.
In my board proposal, I highlighted two important instruments: Atlan and ThoughtSpot. I defined that whereas we may handle with out them, they’d make a big distinction. I wished governance to turn out to be embedded in our processes, and that as a substitute of assigning knowledge stewards with out clear route, we offered actionable reviews and comprehensible knowledge. With correctly organized knowledge, governance turns into simple, and Atlan streamlines this course of.
I chosen Snowflake for its robustness and affordable pricing, and Fivetran for its dependable pipeline efficiency, which successfully handles our knowledge integration wants.
I carried out PowerBI for government reviews, and ThoughtSpot for our self-serve knowledge wants. I’m an enormous fan of ThoughtSpot, as a result of it permits customers to regulate their very own reviews, lowering the necessity for fixed modifications from the information workforce.
For orchestration, I exploit Airflow to handle pipelines, and DBT with GitLab for our code repository and CI/CD processes.
Why was Atlan a very good match? Did something stand out throughout your analysis course of?
In my earlier group, I attempted utilizing open-source with DataHub, however its upkeep and growth required vital funding. Atlan stood out as a result of it’s plug-and-play, mechanically constructing out miners that reveal beforehand unknown insights. It identifies and explains scripts we weren’t conscious of, saving time and lowering technical debt from having to manually overview in depth code.
Atlan lets us monitor and monitor what we’ve constructed, together with knowledge lineage and belongings. It’s invaluable for reviewing reviews while not having to ask for code particulars—simply navigate via Atlan to see the report’s historical past. New workforce members can even perceive report development via Atlan.
For me, Atlan was a key piece of the puzzle.
I researched Collibra, Alation, and Atlan extensively, and Atlan was the clear selection. It felt designed for medium-sized enterprises and required minimal engineering effort. Given our scenario, it was essential to combine it from the beginning, relatively than as an afterthought. This allowed us to study and develop Atlan alongside our present methods, relatively than attempting to pressure it into our pre-built setup.
I all the time make it a degree to fulfill with management groups at occasions to gauge their perspective and willpower, and I don’t know of another gamers which might be doing it in addition to Atlan. I used to be genuinely impressed by Atlan’s management workforce — not solely their ardour for the product but additionally their dedication to addressing my challenges and enhancing our scenario.
How are you planning to harness Atlan to reinforce your knowledge stack? What thrilling use instances and targets do you take note of?
We’ve invested in an information vault mannequin for our knowledge warehouse, which feeds into an operational knowledge retailer, what I name the information mart. All our reviews and metrics are constructed from this knowledge mart. In Atlan, we outline the best way to assemble all the pieces, so as soon as a metric is outlined, we will write the SQL to extract it from the mart.
We then create curated tables for consumer providers and gross sales organizations, enabling them to self-serve by way of ThoughtSpot. For detailed insights into the development and rationale of those metrics, we retailer that data in Atlan, which turns into our catalog.
As new individuals come on board, I make sure that there’s no want for a handover. By default, we doc our processes as we go and construct methods that go away clear breadcrumbs for others to observe. Atlan performs an important function on this. We direct new workforce members to Atlan to assist them perceive how all the pieces is constructed and what it’s constructed from. Atlan doesn’t simply spill out the code, it highlights the important thing objects, their utilization, and their significance.
One other main challenge entails making a complete glossary inside Atlan, serving as our single supply of reality. This surroundings permits enterprise customers to entry all company metrics and think about reviews from Salesforce, PowerBI, and ThoughtSpot, all linked round key KPIs.
We’re additionally at the moment refining our knowledge lineage and mannequin descriptions. As we create new knowledge fashions, we replace descriptions incrementally relatively than in bulk. This ongoing effort helps make sure that our knowledge fashions are well-documented and simply comprehensible.
Do you might have any recommendation to share together with your friends who’re beginning out in managing and organizing their knowledge belongings successfully?
Companies all the time speak about being knowledge pushed, however they don’t discuss concerning the belongings that truly drive the information. We wish data to movement in our group, however data can not movement if it’s not organized constantly. And for me, instruments like Atlan are making it considerably simpler for us to arrange and talk what knowledge issues.
Don’t get me unsuitable, Atlan isn’t a silver bullet. It gained’t repair poor group inside your knowledge warehouse. Nonetheless, it does present a centralized place to outline and assess your processes, serving to you determine which of them are efficient and which of them want enchancment.
Atlan helped us decide the place to start out by figuring out our most vital tables and specializing in what was vital. As an illustration, we discovered one desk important for all the pieces we constructed, permitting us to prioritize it. We then assessed our reviews and found that some we thought had been vital had been related solely to particular reviews, not the broader context.
As we get delicate knowledge, we will additionally instantly flag it. If we get audited, we will merely pull up Atlan and say, “Hey, that is what we’ve. That is how we handle our knowledge. That is what our knowledge belongings are.” So, for these dedicated to being data-driven, they should take care of their knowledge belongings and perceive what their knowledge belongings are.
Photograph by Adi Goldstein on Unsplash
