Pay rates for data science jobs and trends in programming languages are revealed in a new report.
Data is becoming increasingly important to success in the digital economy and data workers spend the majority of their work week on data activities.
Users across all geographies, company sizes, industries and departments use data. They have to overcome skills gaps, learn and use multiple tools to work with data.
More time is being spent on analytics than on data science or application development yet searching for and preparing data are the most frequent and the most inefficient activities.
Irving, CA-based analytics platform Alteryx and IDC recently released a report showing how, despite innovation, time is wasted as workers search for the data they need.
The State of Data Science and Analytics report shows that data workers spend 90% of their working week (around 36 hours) on data-related activities such as searching, preparation and analytics.
Searching for and preparing data are the most common activities of the data worker role at 15% and 33% respectively. On average, they use four to seven different tools to perform data activities, adding to the complexity of the data and analytics process.
Organizations are suffering from inefficiencies and ineffectiveness as they turn to data as the lifeblood of their digital transformation — and the workforce is struggling.
About 54M data workers around the world face challenges associated with the complexity, diversity and scale of their company’s data. These data workers represent a quarter of knowledge workers around the world.
Four out of five (80%) of organizations take advantage of data across multiple organizational processes, but despite increases in innovation, workers waste 44% of their time each week due to unsuccessful activities because of lack of collaboration, existence of knowledge gaps and resistance to change.
On average, data workers leverage more than six data sources, 40 million rows of data and seven different outputs along their analytic journey.
The top frustrations cited by data workers in the survey are indicative of root causes that are responsible for inefficiencies and ineffectiveness. For example, more than 30% of data workers say they spend too much time in data preparation, a task that can often be automated.
Almost nine out of ten (88%) of data workers, approximately 47 million people worldwide, use spreadsheets in their data activities. Spreadsheet functions are often used as a proxy for data preparation, analytics and data application development tools but are error-prone and expose the organization to compliance and trust issues.
The most used spreadsheet functions by 50-70% of users include data summarization, date/time manipulation, transpose, lookup, and conditional formulas.
A third (33%) of workers reckon that they waste too much time preparing data, and almost three out of ten (29%) suffer from slow response times to their requests. Only one in five (22%) cite a lack of understanding of analytics and data science as an issue.
Alan Jacobson, chief data and analytics officer (CDAO) of Alteryx said: “As the data landscape becomes more complex, this survey exposes the tip of the iceberg when it comes to the sheer volume of workers needing to conduct analysis on a daily basis and the untapped potential for them to drive meaningful business impact.”
We rely on social media and smartphone apps, from dating and connecting to online shopping and browsing the web. We constantly give out private data online — but what exactly do we share with these platforms?
Gen Z — the born-digital generation — expects a “more human” experience online. So, if this is true, the bigger question for future generations is what it means to be human in a digital world.
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Workers waste half their time as they struggle with data
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