How To Turn Your Data Into Insights

At a glance Discover how to transform your structured and unstructured data into valuable insights. Dive into our helpful tips for leveraging data to boost your brand or client.

We swim in a sea of data. How can you take your data and turn it into intelligence you can use? There are two main types of data: structured and unstructured. Structured data follows a specified format and requires processing to produce. Aggregated numbers/data points are a great example of structured data. Conversely, unstructured data doesn’t follow a specified format, but this is the individual data behind your structured data. This is text, tweets, photos that provide context to your structured data. Structured data provides you with the what is happening, while unstructured provides the why. Both are important for turning data into insights. Here we share our tips for turning both types of data into insights in various areas that impact your brand or client. Get started by aggregating all your data in one place here.

Nicky Yates Published on October 5, 2016 2:57 pm

Frequently Asked QuestionsFAQs

What is the difference between structured and unstructured data?

Structured data follows a specified format like aggregated numbers and data points, while unstructured data doesn't follow a format and includes things like text, tweets, and photos. Structured data shows you what is happening, while unstructured data provides context for why it's happening.

How do you turn data into actionable insights?

Start by aggregating all your data in one central location to get a complete view. Then analyze both structured data (the 'what') and unstructured data (the 'why') together to understand the full story behind your metrics.

Why do I need both structured and unstructured data for insights?

Structured data alone only tells you what happened, like traffic numbers or engagement rates. Unstructured data like social media comments and reviews provides the context and reasoning behind those numbers, giving you a complete picture.

What are examples of unstructured data for brand analysis?

Unstructured data includes social media posts, customer reviews, comments, photos, and any text-based content that doesn't fit into neat categories. This type of data provides valuable context and sentiment that explains the trends you see in your structured data.