The practice of digitally collecting data by companies can be traced back to the 1980s, with the introduction of relational databases. Since then, organizations have accumulated colossal amounts of data, and this trend shows no signs of slowing down. In fact, it is estimated that data collection will reach an astounding 181 Zettabytes by 2025.
We’ve all heard data described as ‘the new oil‘. However, much like oil, data isn’t inherently valuable, until it is collected, refined, and applied. For companies that constantly evolve and optimize their data strategy, their data becomes an ever-appreciating and compounding asset.
Since the 1980s, we have witnessed several transformative advancements such as data warehouses, SaaS, and cloud-based data warehousing. In recent years, the way companies interact with and consume data has changed forever. As a result, companies that leverage their data to fuel growth through data-driven insights are reaping even greater rewards.
While gathering data is the first step, the real business value lies in transforming it into valuable, actionable insights. Companies that embark on a data journey and recognize this fact will discover a plethora of opportunities to strike gold along the constantly evolving path.
Data Journeys can be broken into 3 equally important parts:
The first step, once you have ‘unsiloed’ and gathered all of your data, involves making that data consumable. Companies today live in a very data-siloed world. The average technology company uses 155 cross and intra-departmental business applications, all generating reams of data in their own disconnected repositories.
In order to gain actionable insights, you must create a single source of truth that brings together all of this trapped and siloed data. This is where the data warehouse comes in. While the data warehouse is nothing new, the way in which companies are interacting with it has changed significantly. The modern data warehouse has become the beating heart of any organization taking the modern Data Journey.
Once that single source of truth has been established, the true journey begins, but without completing this crucial first step, you will remain grounded. In order to leverage the data in this single source of truth, companies typically use a Business Intelligence (BI) tool to create dashboards and reporting across their teams and divisions.
With dashboarding in place, the entire company now has an accessible, visible, and consumable way to leverage all of their data for making true data-backed decisions.
By this stage of the journey, companies had traditionally reached the ‘promised land’ - their executives could see overall company performance, Sales leaders were tracking their pipelines, and Marketing finally had their CAC, CAC Payback, ROAS, and Cost Per Lead-by-channel in customizable visual formats.
And while these dashboards proved to be very useful, users and teams started to ask “Can we get some of the data into the platforms and apps we use every day?”.
You can see the appeal - what if Sales could see who were the most active and least active prospects directly, in their CRM? What if Marketing were able to create personalized emails based on specific actions users took in their trial accounts? And what if Customer Support could have all of their customers’ subscription, plan, and activity information visible in their support platform to inform them about churn risk and expansion opportunities?
And so the second stage of the Modern Data Journey was born - operationalizing your data! Along with the necessary technology to get there.
Companies and teams who make it to this stage often think, “how in the world did we even survive without leveraging our data like this?”. Dashboarding is a critical component of any business, but empowering your teams by giving them the data they need, where they need it, when they need it, is a truly business-changing event.
The final step on today’s Modern Data Journey revolves around making your treasure chest of data accessible by your teams and clients who need and want it the most.
While the use cases around this step are endless, a couple of the most common areas customers see value are:
Data Sharing - With both internal and external parties. Sure, sharing data over and back via CSVs and spreadsheets work, but when your data is available and easily accessible via APIs, it instantly becomes orders of magnitude more valuable.
Building Data Products - A data product can be defined as an application that is powered with data from your data warehouse. Yes, a BI reporting tool could be classified as a data product, however, the data products we see companies building at this stage are more specific to their own needs and their customers’ needs. For customer-facing data products, this often provides an opportunity to create new revenue streams for the company.
Imagine you're a coach for an MLB team and you’ve built a state-of-the-art Data Science team (congratulations, Billy Beane!) to predict and model your team’s performance. Your team wears heart rate sensors and GPS trackers during training, sleep monitors at night, and track food intake during the day.
Your Data Science team then creates ML models to predict player performance to the minute based on all of the data inputs. While it’s great that you have these models in your single source of truth, wouldn't it be great if you could view it in an app on your phone or iPad during every training and MLB game to help you win more games?
Yes? Then it sounds like you need a data product built for you!
While the data journey is a long and winding path, the incremental value of a company’s data grows exponentially as they advance down that path. With the right resources and support, the Modern Data Journey is achievable for every company. The first step is always the hardest, but the secret to getting there is… to just get started!
The data journey is a forever-evolving path. What’s the next step on this journey you may ask? We could be seeing the next stage of the data journey play out before our eyes -
AI/ML have been talked about for years but we are just now starting to see these become consumable and useful for modern day companies through generative AI applications like ChatGPT, Bard, MidJourney, and many many more.
What do you see becoming the next stage of a company’s data journey?