The art of Data interpretation starts with Excel

Data interpretation, this is how you do it!

As our data-driven economy continues to evolve, the volume of data we handle has grown exponentially.  While electronic spreadsheets like MS Excel help organize and visualize data, true data interpretation goes beyond simple spreadsheets. That is why we offer various models to interpret data. This article breaks down data interpretation in an easy-to-understand way, offering practical models to make sense of your data. At EasyData, we don’t just provide software — you have direct access to data specialists who can guide you through your project. Our technology aims to make your future data interpretation challenges a lot simpler to handle.

Data interpretation in Excel

We don’t rule out Excel—it remains a valid tool for many cases.

Our goal is always to find the best solution, which sometimes means using familiar platforms like Excel, Google Sheets, or similar tools that fit your workflow.

Data recognition via a simple metaphor

Suppose you are new to the world of data interpretation. consider this analogy: Imagine your car’s fuel gauge or battery indicator. When the level drops too low, the car stops. You rely on this information to decide how far to drive and when to refuel. This is a fundamental example of data analysis.

Keep your data interpretation simple

Data interpretation in the workplace should function similarly to the metaphor cited above – providing clear, actionable insights.  When data is presented in a way that requires minimal effort to understand, it keeps your decision-making simple.

Data Science applied

Our expertise lies in identifying patterns by sorting data and cross-referencing multiple data sources, including complex external datasets. Our passion is transforming raw data into visualized patterns and trends with practically applied Data Science.

Decision making

Ultimately, decision-making rests with the user—whether policymakers, managers, or executives. Our role is to provide accurate, well-structured data to support informed decisions.

Data-driven decisions

Let’s take the stock market as an example. Prices fluctuate daily—so if a stock drops, should you sell immediately? To be able to make this decision, you need knowledge and experience. Visual data interpretation will then help you to gain insight into the price trend over a longer period.

Making decisions with a limited amount of data is an error prone strategy.

Experience with data interpretation

Your expertise is crucial in interpreting data. If you understand which external factors influence stock prices, they should be included in your considerations as an external dataset. How do you do that? It’s EasyData’s job to present this data in a way that makes it easier for you to analyze and act on. Naturally, you can find much more data about the subject on the Internet.

Data interpretation with meaningful results

We often see dashboards or reports with unclear or useless data presentations.

A key question to ask is: Do the findings hold up under significance testing? While pleasing numbers may satisfy a client, true data interpretation must be based on accuracy and reliability.

Data interpretation in elections

The day before Donald Trump’s election victory, many predicted it was impossible. The data supporting each candidate was interpreted differently, leading to vastly different conclusions. The Guardian has published an in-depth article on this topic.

Machine Learning with Your Data

We take a different approach — using Machine Learning (ML) to uncover trends with the datasets validated by EasyData. Our algorithms can highlight gaps or misclassifications, allowing data to be refined and retrained to add value to your project.

Stick to your data

The relevance of Machine Learning models is evident from the results that we share with our clients. Suppose we opt for a Web scraping approach to arrive at a fully relevant data set. If we use Web scraping to build a relevant dataset, we optimize search queries to ensure the best Data Capture. This also requires keeping close communication with clients during algorithm development.

Ideal interpretation of data

In an ideal scenario, all data is automatically collected, processed by an algorithm, and presented in an agreed format. In practice, this is often a bit more difficult. Sometimes data is collected from sensors, surveillance footage, or from poor quality images via OCR. EasyData has solutions for these scenarios, as well for automation of data entry processes to improve efficiency. With EasyData technology, the realization of such projects is enormously facilititated!

Want to know more about data interpretation?

We’d love to discuss how we can help with your data interpretation needs. Contact us for a Teams meeting, or visit us in Apeldoorn to see how our expertise can add value to your organization.