Inspired by a book by Haruki Murakami, the title sums up well what often plagues the data analysis debate: we often find ourselves discussing disparate concepts. Some view data analysis as reporting, while others relate it to modeling or calculations.
Some people discuss visualization and some see it as finding answers from data. Trimble values all of the above mentioned elements. Still, believes that the true essence of data analysis lies elsewhere and human creativity is the key element.
In this article, the company presents its perspective on this subject. Trimble is not suggesting that other definitions are incorrect, but it’s essential to define precisely what means when discussing data analysis.
What is data analysis?
Data analysis takes on various definitions; Trimble is as follows: data analysis is when you use creative data processing methods to uncover answers to novel questions or to provide explanations for unfamiliar scenarios.
Data analysis can be helpful in situations you don’t know the answer and it cannot be predicted. Next, Trimble wants to break this definition into smaller parts and specify the creative data analysis components.
The elementary components of creative data analysis
1. Ask new or random questions
A new question is one in which a ready-made model or answer is unavailable. For example, if something is happening for the first time or the environment has changed, we face a new challenge. If the same question arises repeatedly, creating an automated system that can provide the answer may be more efficient. This could be a reporting system, an automation system configuration or something else.
2. Collect and refine the data to find the answer
Collect data with an open mind and in manageable amounts. Attempting to gather all data is not feasible and will likely result in drowning in data. On the other hand, limiting the raw data to the obvious will not lead to new insights. Raw data includes all available information but is mostly useless without cleansing.
Data must be refined to reveal meaningful characteristics to find answers to specific questions. The refinement process depends on the question and the raw data’s nature. When we want to find answers to random questions from unknown data, analysis requires a creative element to be successful, as predefined sequences often do not work well enough in new situations.
3. Learn along the way
When you process data through creative cleansing, refining, calculations and analysis methods, new information and insights inevitably emerge. This guides your data analysis forward. Often, these new insights result in redefining the original question.
For instance, we once participated in a project to reduce production costs. However, the result was increased production speed and yield, breaking production and efficiency records.
4. Let the data speak for itself
Owing to the creative refinement process, the answers obtained through data analysis are often unpredictable. Meaningful data analysis requires domain knowledge, and analysts tend to have their favorite methods of data refinement, which can sometimes lead to biased thinking.
A smart data analyst lets the data speak for itself and provide the information it holds. In contrast, poor analysts may manipulate the data to support their preconceived assumptions and hypotheses.
Data analysis is an enabler; creative humans bring value
Curious and creative individuals who enjoy seeking solutions to complex questions are valuable assets to any company and can’t be ignored when looking for the payback of any data analysis work and system. Data analysis alone provides no payback or value; it’s an enabler.
The value is generated when you use the results from creative data analysis to change human operations, reconfigure automation systems, modify recipes, etc.
The outcomes and results of creative data analysis are unpredictable as they find answers to random questions. Despite this, data analysis is critical to every company’s success. With creative data analysis, you can gain new insights and make better and more accurate decisions faster.
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