Kent’s collaboration with Fusion Analytics underscores the power of integrating tailored insights into decision-making. By bridging the gap between internal data and industry-wide benchmarks, Fusion empowered Kent to make strategic, goal-oriented changes. The result? Measurable growth, optimized resource allocation, and a business poised to capitalize on future opportunities. Driving Strategic Growth: How Kent Partnered with […]
Executives and data users frequently express frustration with current solutions that present data in a cluttered, non-intuitive manner – the data chaos. This barrier prevents Meaningful Metrics from shining and contributing effectively to business decisions. Previously, we talked about the benefits of Synchronizing metrics and data into a decision-driven framework, where everything is linked back […]
Read More… from Visualizing: Seeing the Power of Decision-Led Metrics
There are common changes that can influence the truthfulness of data: Typically, changes in metrics or data result in a noticeable shift in the trend, rendering new data points incomparable to older ones. This disparity leads to another form of data chaos – lack of comparability. Many may question – “Does this mean I need […]
Read More… from Equalizing: Ensure Comparability within Business Dynamics
In our experience working with various companies, we often observe that different departments lack access to the complete suite of metrics and data crucial for informed decision-making. For instance, consider a scenario where Marketing recently ran a campaign and the CEO wants to know its effectiveness. The Marketing team’s report showed an increase in brand […]
Read More… from Synchronizing: Connecting Metrics to Your Key Decisions
Filtering data sources using Fusion Analytics’ AI Data Enrichment Engine is the first step in eliminating data noise. However, that alone is not sufficient. Individual data sources can contradict each other when viewed in isolation – the bias and disjoint between data sources within Data Chaos. Every department may have its own lens on business […]
A decade ago, the challenge was obtaining sufficient data for analysis. Today, businesses face a different issue: data chaos. The proliferation of large Data Lakes has resulted in a daunting mountain of contradictory data that is noisy, biased and disjointed. Leading with Decisions helps streamline the identification of necessary metrics and data sources essential for […]
Read More… from Filtering: The Initial Step To Turn Raw Data Into Meaningful Metrics
In conversations with executives and data users, Fusion Analytics often challenges related to their massive Data Lakes – “The data is noisy, biased and disjointed. I don’t know what to do with it.” To address this Data Chaos, begin by asking “What decisions am I trying to make?” For instance, you would like to know […]
Read More… from Metrics: Right Metrics Leading to Right Data
Today, many companies maintain massive Data Lakes comprising of diverse data sources with varying methodologies, frequencies and depth. Working with this data can be chaotic due to its raw, noisy, biased, and disjointed nature. Consequently, it’s challenging to integrate everything cohesively and derive meaningful insights. Many executives and data users often ask: “What should I […]
Read More… from Decision-Led Mindset: Aligning the Right Input to Output
Many companies today manage massive Data Lakes filled with diverse data sources that vary in methodologies, frequencies, and depths. However, this data often remains raw, which introduces noise, biases, and disjointedness and pollutes the Data Lake. Due to the disjointed nature of these data sources, they are typically presented in isolated reports. This results in […]