Unifying a Information Stack and Leveraging Self-Serve Analytics with Atlan
The Energetic Metadata Pioneers sequence options Atlan clients who’ve accomplished a radical analysis of the Energetic Metadata Administration market. Paying ahead what you’ve discovered to the following information chief is the true spirit of the Atlan group! In order that they’re right here to share their hard-earned perspective on an evolving market, what makes up their trendy information stack, revolutionary use circumstances for metadata, and extra.
On this installment of the sequence, we meet Daniel Ferguson, Information and Analytics Director at PHMG, an audio branding firm that helps over 36,000 shoppers throughout 56 nations sound their greatest. Daniel shares how PHMG remodeled their information stack from fragmented to unified, and the way Atlan has been a vital piece in by monitoring lineage, managing stories, 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 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 aspect of issues. After beginning a household, I needed 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 middle unit, dealing with calls. It rapidly turned obvious that I might do extra than simply calls, so I moved to the database group.
I began finding out 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 individual, I might obtain the identical outcomes as the whole group. My work generated 300% extra outcomes than the group’s mixed efforts by optimizing information assortment, addressing lacking info, and cherry choosing one of the best contacts. After that I used to be hooked on the ability of information & analytics.
I then constructed an organization offering information 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 shoppers like Sony, Workplace Depot, and RBS, which gave me early publicity to the info career. From there, I superior within the discipline and ultimately joined PHMG. My journey into information was considerably unintended, however it introduced me to the place I’m in the present day.
Would you thoughts describing PHMG?
We specialise in audio branding. Consider logos like Netflix or Disney Plus, by way of sound alone, these manufacturers are immediately recognizable as business leaders in leisure and streaming even when their visible logos should not in sight.
We additionally transcend conventional audio branding by creating 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 desires to carry?
This connection between music and identification is what attracted me to the corporate. We’ve been extremely profitable, working in 56 nations with 36,000 shoppers.
Might you describe your information stack, and the way it got here collectively?
After I received right here, we have been utilizing SQL servers with Excel spreadsheets. There have been restricted to no interactive stories, and each information request needed to be raised to the info group.
There was a have to modernize the data flowing into the corporate and implement the appropriate know-how to attain this effectively and reliably. I centered on discovering know-how options that might streamline operations and scale back the necessity for added 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 presents a complete answer, 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 one of the best instruments for the job and guarantee they work effectively collectively. Investing in a seamless course of with these instruments means that you can 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 might handle with out them, they’d make a big distinction. I needed governance to change into embedded in our processes, and that as a substitute of assigning information stewards with out clear route, we supplied actionable stories and comprehensible information. With correctly organized information, governance turns into easy, 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 information integration wants.
I carried out PowerBI for govt stories, and ThoughtSpot for our self-serve information wants. I’m an enormous fan of ThoughtSpot, as a result of it permits customers to regulate their very own stories, decreasing the necessity for fixed modifications from the info group.
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 improvement required important 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 decreasing technical debt from having to manually overview in depth code.
Atlan lets us observe and monitor what we’ve constructed, together with information lineage and property. It’s invaluable for reviewing stories while not having to ask for code particulars—simply navigate by way of Atlan to see the report’s historical past. New group members may also perceive report building by way of 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, fairly than as an afterthought. This allowed us to study and develop Atlan alongside our current programs, fairly than attempting to power it into our pre-built setup.
I all the time make it some extent to satisfy with management groups at occasions to gauge their angle and dedication, and I don’t know of some 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 in addition their dedication to addressing my challenges and enhancing our scenario.
How are you planning to harness Atlan to boost your information stack? What thrilling use circumstances and objectives do you take into account?
We’ve invested in an information vault mannequin for our information warehouse, which feeds into an operational information retailer, what I name the info mart. All our stories and metrics are constructed from this information mart. In Atlan, we outline the best way to assemble every little thing, 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 info in Atlan, which turns into our catalog.
As new individuals come on board, I be sure that there’s no want for a handover. By default, we doc our processes as we go and construct programs that go away clear breadcrumbs for others to observe. Atlan performs a vital function on this. We direct new group members to Atlan to assist them perceive how every little thing 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 mission includes making a complete glossary inside Atlan, serving as our single supply of fact. This setting permits enterprise customers to entry all company metrics and look at stories from Salesforce, PowerBI, and ThoughtSpot, all linked round key KPIs.
We’re additionally at present refining our information lineage and mannequin descriptions. As we create new information fashions, we replace descriptions incrementally fairly than in bulk. This ongoing effort helps be sure that our information fashions are well-documented and simply comprehensible.
Do you’ve got any recommendation to share along with your friends who’re beginning out in managing and organizing their information property successfully?
Companies all the time speak about being information pushed, however they don’t speak in regards to the property that truly drive the info. We wish info to circulate in our group, however info can’t circulate if it’s not organized persistently. And for me, instruments like Atlan are making it considerably simpler for us to arrange and talk what information issues.
Don’t get me mistaken, Atlan isn’t a silver bullet. It received’t repair poor group inside your information warehouse. Nevertheless, 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 vital. As an illustration, we discovered one desk crucial for every little thing we constructed, permitting us to prioritize it. We then assessed our stories and found that some we thought have been vital have been related solely to particular stories, not the broader context.
As we get delicate information, 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 information. That is what our information property are.” So, for these dedicated to being data-driven, they should take care of their information property and perceive what their information property are.
Photograph by Adi Goldstein on Unsplash
