What is Analytical Harmony and Why Do You Need It?

Harmony is when different instruments play different notes, but together they create a beautiful, satisfying, balanced sound that all works together. Conversely, discord is when these notes and instruments clash to produce what sounds like confusion and chaos. When it comes to how various teams align with and use their data, some teams are in analytical harmony — unified goals, clear communication, and working together — while other teams suffer from analytical discord.

Not being in agreement on even the simplest of definitions or measurements can eventually cause massive misalignment. For example, imagine half of your team measures the length of a day when the sun crosses a particular position relative to a position on Earth (a solar day). Imagine the other half of your team measures the length of a day using the position of a star instead of the sun (a sidereal day). While they're both measuring the length of a day (supposedly), measuring by a star makes the day four minutes shorter. This may not make a big impact on the first day, but six months later both measurements — and teams — will be wildly misaligned.

Unfortunately, many organizations often approach their data in much the same way, with unaligned terms, definitions, and rules, leaving teams unable to align and organizations hard to scale. But when it comes to aligning your teams around a better data strategy, Ojha says, "They want to understand what are they going after and how are they going to measure their success? How are they going to measure their distance from their goals? People need to have a common understanding of what they are measuring and how they are measuring it."

How can you bring everyone into analytical harmony?

The Challenges of Taking a “Dataset First” Approach

Many organizations take a "dataset first" approach, which starts with an analyst writing some SQL code that produces a dataset. Next, an application will generate a model from that data set to understand what's in the dataset. Then, the application will build reports and dashboards around what it finds.

The problem with this approach is that it's hard to keep everyone aligned, particularly when an organization wants to scale. Having one analyst create a dataset may not be a challenge, but as an organization scales, they may have upwards of a hundred analysts creating hundreds or thousands of datasets and dashboards. As this complexity grows, it becomes difficult to maintain a consistent set of analytics with the same terminology and definitions.

Additionally, if something changes — a policy or definition, or an error needs correction — organizations must scramble to find all instances that need changing across all those datasets, resulting in further misalignment, potential error, and discord.

How MicroStrategy's Semantic Graph Achieves Analytical Harmony

MicroStrategy takes a "model first" approach to data by using a semantic graph. In this approach, extracting the data doesn't come first. Instead, building a model comes first, along with understanding where the data sits, what the data should be called, and any necessary business rules or logic. Once that’s in place, then the MicroStrategy platform will create the dataset. The platform will also write the SQL for you, which means anyone can access the data they need — not just those who know how to code.

"The idea here," explains Pham, "is that we want to get people information and analytics using a common set of terminology, business definitions, and business rules in a way that is scalable."

The benefits gained from using a semantic graph are many, including:

• More data accessibility: "Intelligence everywhere" is MicroStrategy's mission, in that everyone should have access to the data they need — whether it be a C-suite executive, a delivery driver, or a store manager. By providing access through a flexible semantic graph, anyone can gain insights that are specific to their data needs.

• Increased transparency: Instead of using a platform that's a black box or where initial instructions are all in code, MicroStrategy allows anyone to understand the components that make up their reports, tracking how the information was delivered to them.

• Enhanced data security and privacy: With a centralized semantic graph, organizations can have better control over how their data is stored and who can access their sensitive data, increasing data protection and security.

Singing in Harmony Starts Today

Does your organization operate in analytical harmony or are you scrambling with a “dataset first” strategy? With MicroStrategy's semantic graph, your organization can more easily work towards the same goals in a unified, informed, and harmonious way.

Watch the full webinar here. Ready to learn more about MicroStrategy's semantic graph capabilities? Start your 30-day trial today.