Paradox of Story Telling & Data

Data and Story Telling are two inherent components of any Analytics Initiative. Its very important to understand what the Analytics initiative entails – basically the end objective. Many a times, a simple answer to the 3 questions below could provide a lot of clarity on the end goal
1. Are we trying to tell a story using Data?
2. Are we trying to use the data to tell a story?
3. Or do we need both?

Though the above 3 questions look very simple, they have completely different expectations from data.

Question 1 above generally is meant for executives. When they present something, they would already have a view of what they want to present and will need data to align to their expectations. And sometimes, this will be a moving target depending on when we present and what we present. This requires proper data intensive platforms to store, clean and present the data in a cohesive form to tell a proper story. This is more business centric and data platform driven.

On the other hand, Question 2 is slightly different where the end objective is to make the data talk. This will require employing different techniques like Visualizations, Data Mining, Outlier detection, What Ifs etc to make the data tell a story.

In most cases, the requirements can swing between the 2. Sometimes we might want to present our story using the data while sometimes we might want to make the data provide insights. Either way, Data is like Human – you torture it long enough, it will confess!!!!

For both the above use cases, we need a solid platform that can provide the following

1. Data Segmentation, Quality & Consistency
2. Analytics & Visualization with compelling story boarding
3. Extensible backend to provide insights and apply AI/ML to data to find out outliers
4. Alignment of Business Data to Operational Data with meaning business mapping features

We strongly believe, QuarkCube Platform provides all the 4 above to give a consistent, qualified view of data to executives.

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