Overview Public administrations today are tasked with managing massive volumes of data in multiple formats, often using different management methods, as per the demands of their individual organisations. It’s also become common for them to host multiple copies of that data across different repositories. As a result, the data can often be disseminated across multiple regions, especially in terms of content and presentation, unless it is ‘harmonised’. This is one reason why there is so much re-use at the low level of existing information on citizens and businesses, for example.
More than thirty years ago, John Naisbitt put into words a feeling many of us recognise today in “Megatrends,” saying, “We are drowning in information but starved for knowledge.” This statement is incredibly relevant in today’s world, filled to the brim with data for research, analysis, and making decisions. The job of pulling and refining data from questionnaires is key, as these are so many insights and so much valuable feedback.
Harmonizing Data in Biopharma In the biopharmaceutical sector, the collection and analysis of data from diverse sources—clinical trials, real-world evidence (RWE), patient registries, and more—are fundamental to drug development, regulatory approval, and post-market surveillance. However, data from these sources often vary in format, nomenclature, and measurement standards, making it challenging to aggregate and analyze them effectively. Data harmonization addresses these challenges by standardizing disparate data for seamless integration, analysis, and interpretation.
How to Harmonise Questionnaires - 10 Practical Steps (+ 1 Bonus Tip) Data privacy is a big challenge today. It’s all about what we share and what we don’t. Zoher Karu said it well: “One of the biggest challenges is around data privacy and what is shared versus what is not shared. And my perspective on that is consumers are willing to share if there’s value returned. One-way sharing is not going to fly anymore.
Comparing Apples to Oranges: How to Analyse Two Completely Different Surveys So, you’ve created a survey (or multiple surveys), convinced people to take part and answer your questions, and have received the results. Great job! Yet, the real test comes when it’s time to make sense of these survey findings. Today, we’ll take a look at why you need surveys, how to design effective surveys, how to analyse survey data, how to analyse survey data with multiple responses, and how to do data harmonisation when you’re dealing with multiple surveys.
Data Harmonisation Tools – Overview Organisations typically collect data from multiple sources and for many different reasons. This data comes in various forms and formats – for example, it may be coming from market research, customer research or inter-organisation departments. Data harmonisation, an advanced technique used to make sense of all the raw data collected and uses for research purposes, becomes necessary in this case, but unless it is incorporated effectively, organisations might miss the full, holistic view of business performance that they wish to gain.
