Unifying a Knowledge Stack and Leveraging Self-Serve Analytics with Atlan
The Energetic Metadata Pioneers sequence options Atlan prospects who’ve accomplished an intensive analysis of the Energetic Metadata Administration market. Paying ahead what you’ve realized to the following 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, modern use circumstances for metadata, and extra.
On this installment of the sequence, we meet Daniel Ferguson, Knowledge and Analytics Director at PHMG, an audio branding firm that helps over 36,000 purchasers throughout 56 international locations sound their finest. Daniel shares how PHMG remodeled their knowledge stack from fragmented to unified, and the way Atlan has been an important piece in by monitoring lineage, managing reviews, and easing group onboarding.
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?
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 aspect of issues. After beginning a household, I wished a change. After promoting my recording studio, my mom, who managed a council workplace, provided me a job and I began out within the name middle unit, dealing with calls. It rapidly turned obvious that I may do extra than simply calls, so I moved to the database group.
I began learning for a level in Economics and Mathematical Science at The Open College whereas working on the council. Utilizing the talents learnt on my diploma I began to construct logistic regression fashions to focus on contacts within the name middle I had beforehand labored in. I proposed that, with only one particular person, I may obtain the identical outcomes as the whole group. My work generated 300% extra outcomes than the group’s mixed efforts by optimizing knowledge assortment, addressing lacking data, and cherry choosing one of the best contacts. After that I used to be hooked on the ability of knowledge & analytics.
I then constructed an organization offering knowledge providers to different Native Authorities. Close to the top of my diploma, a consultancy in Scotland, Aquila Insights, provided me a place. They labored with purchasers like Sony, Workplace Depot, and RBS, which gave me early publicity to the info occupation. From there, I superior within the area and ultimately joined PHMG. My journey into knowledge was considerably unintentional, however it introduced me to the place I’m right this moment.
Would you thoughts describing PHMG?
We focus on audio branding. Consider logos like Netflix or Disney Plus, by sound alone, these manufacturers are immediately recognizable as trade leaders in leisure and streaming even when their visible logos are usually not in sight.
We additionally transcend conventional audio branding by growing customized music tailor-made to every group. We’ll take Atlan for instance: What’s Atlan about? What do you signify? What’s the kind of rhythm that it needs to carry?
This connection between music and id is what attracted me to the corporate. Now we have been extremely profitable, working in 56 international locations with 36,000 purchasers.
Might you describe your knowledge stack, and the way it got here collectively?
After I bought 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 info group.
There was a have to modernize the data flowing into the corporate and implement the proper expertise to attain this effectively and reliably. I centered on discovering expertise options that might streamline operations and scale back the necessity for extra engineers.
I used to be actually cautious with expertise choice, avoiding options for the sake of it, and never constructing from scratch. Whereas Azure Cloth provides a complete answer, for instance, it’s nonetheless new and that comes with further dangers, however is one thing I’m conserving my eye on. It’s essential to decide on one of the best instruments for the job and guarantee they work effectively collectively. Investing in a seamless course of with these instruments permits you to begin robust and reveal 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 develop into embedded in our processes, and that as a substitute of assigning knowledge stewards with out clear path, we offered actionable reviews and comprehensible knowledge. With correctly organized knowledge, governance turns into easy, and Atlan streamlines this course of.
I chosen Snowflake for its robustness and cheap pricing, and Fivetran for its dependable pipeline efficiency, which successfully handles our knowledge integration wants.
I applied PowerBI for govt reviews, and ThoughtSpot for our self-serve knowledge wants. I’m a giant fan of ThoughtSpot, as a result of it permits customers to regulate their very own reviews, lowering the necessity for fixed modifications from the info group.
For orchestration, I take advantage of 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, routinely 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 evaluate 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 without having to ask for code particulars—simply navigate by Atlan to see the report’s historical past. New group members may also perceive report development by 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, moderately than as an afterthought. This allowed us to be taught and develop Atlan alongside our present techniques, moderately than attempting to power it into our pre-built setup.
I at all times make it a degree to satisfy with management groups at occasions to gauge their angle and willpower, and I don’t know of every other gamers which can be doing it in addition to Atlan. I used to be genuinely impressed by Atlan’s management group — not solely their ardour for the product but additionally their dedication to addressing my challenges and bettering our scenario.
How are you planning to harness Atlan to reinforce your knowledge stack? What thrilling use circumstances and objectives do you bear in mind?
We’ve invested in a knowledge vault mannequin for our knowledge warehouse, which feeds into an operational knowledge retailer, what I name the info mart. All our reviews and metrics are constructed from this knowledge mart. In Atlan, we outline easy methods to assemble every part, 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 shopper providers and gross sales organizations, enabling them to self-serve through 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 be certain that there’s no want for a handover. By default, we doc our processes as we go and construct techniques that depart clear breadcrumbs for others to observe. Atlan performs an important function on this. We direct new group members to Atlan to assist them perceive how every part 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 undertaking entails making a complete glossary inside Atlan, serving as our single supply of fact. This atmosphere permits enterprise customers to entry all company metrics and examine reviews from Salesforce, PowerBI, and ThoughtSpot, all linked round key KPIs.
We’re additionally presently refining our knowledge lineage and mannequin descriptions. As we create new knowledge fashions, we replace descriptions incrementally moderately than in bulk. This ongoing effort helps be certain that our knowledge fashions are well-documented and simply comprehensible.
Do you could have any recommendation to share together with your friends who’re beginning out in managing and organizing their knowledge belongings successfully?
Companies at all times speak about being knowledge pushed, however they don’t speak in regards to the belongings that really drive the info. We wish data to stream in our group, however data can’t stream 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 incorrect, 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 begin by figuring out our most important tables and specializing in what was essential. For example, we discovered one desk crucial for every part we constructed, permitting us to prioritize it. We then assessed our reviews and found that some we thought had been essential 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 got. 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.
Picture by Adi Goldstein on Unsplash
