Oracle: the data science team
We are analysts, data scientists and coders. We deploy traditional and cutting edge treatments to find the edge in the data. It’s more than a data team, senior Oracle time is dedicated to learning new techniques, and driving our understanding forwards. We also do the basics exceptionally well. Our data is different because it goes through layers of automated and human cleaning before we work with it.
Data accuracy
Impactful data is about world-class survey design, data management, checking for over acquiescence, and cleaning; the accuracy of our data is one of our USPs.
The questionnaire will be developed to global best practice to ensure objectives are met in full. Our data science team, Oracle, ensure data is thoroughly cleaned. It’s got to be right to give confidence to progress or to ensure a claim can withstand all legal challenges.
Sweating the details that add up
“Data cleaning is not simply a task of ‘remove bad cases on one question and suddenly everything is perfect’. We aim to stress test and inspect each question and every question type for quality and control. These multiple checks lead to incremental increases in quality, which ultimately provide for a richer and more robust dataset.”
Mike Calvert, Head of Data Solutions
Success stories…
Frequently asked questions
We hope you find these FAQs and short answers useful. If there is anything further that you would like to know, please get in touch via the contact form below.
Key driver analysis is a statistical method used to identify and prioritise the most influential factors or variables that significantly impact a particular outcome or dependent variable. It is commonly used in market research, data analysis, and business strategy to determine which factors have the most significant effect on a target metric. This analysis helps businesses and researchers understand which variables or drivers are critical for achieving desired outcomes and where to focus their efforts for improvement or optimisation.
Data scientists are professionals who extract valuable insights and knowledge from data. They collect, clean, and analyse data using various tools and techniques, often involving programming and statistics. Their work helps organisations make data-driven decisions, develop predictive models, and solve complex problems. Data scientists play a crucial role in fields like machine learning, artificial intelligence, and data-driven research, contributing to informed decision-making and innovation.
Data science is a multidisciplinary field that involves extracting insights and knowledge from data. It combines techniques from statistics, computer science, and domain expertise to collect, analyse, and interpret data to make informed decisions and predictions. Data scientists use various tools and methods to uncover patterns, trends, and valuable information within data sets, often contributing to business, scientific, and social advancements.
A likert scale is a type of questionnaire or survey which uses a rating scale to measure how people feel about a particular topic or subject. It usually includes a series of questions to which respondents are asked to express their level of agreement or disagreement on a scale often ranging from ‘strongly disagree’ to ‘strongly agree’. This quantitative research methodology helps to analyse people’s responses, making it easy to understand and interpret attitudes or opinions on various issues.
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