Alteryx, the analytics automation company, issued findings from an Alteryx-commissioned IDC Infobrief, revealing that approximately 62.4 billion data and analytic work hours are lost annually worldwide – the equivalent to almost 100,000 human lifetimes. While data and analytics power the digital-first enterprise, this study reports 95 percent of organizations are still being challenged by creating analytic outcomes from the terabytes of complex raw data piling up across the business.
As businesses strive to move from being data-hoarders to driving real insights by democratizing analytics, the IDC Infobrief, “Data and Analytics in a Digital-First World”, reveals how complexities, constraints, skill gaps, and a lack of analytics automation are hurting productivity.
The challenge of democratizing data and analytics in a digital-first world
Despite 70 percent of organizations citing wanting to be more data-driven now than before the pandemic, 88 percent of respondents still face technology constraints, and 95 percent struggle with operational challenges around data and analytics. Of the 78M advanced spreadsheet users worldwide, data-native workers report they are losing 800 hours annually due to due to 61 percent of data activities still being completed in inefficient legacy spreadsheets. Among other key findings from the global study of data workers’ activities:
- A lack of analytics automation is harming data native productivity. Of the 61 percent of data workers who perform activities in only spreadsheets, 27 percent of their time is spent repeating the same or similar activity steps every time a data source has been updated or refreshed. The equivalent to on average seven hours per week.
- Data and analytics complexity illustrate the need for skills and technology improvements. For example, data natives process highly distributed, diverse, and dynamic data at scale from an average of four unique sources per analytic input and 6.6M rows of data to deliver an average of four unique analytic assets for consumption.
- The data and analytics experience needs to be improved as 91 percent of organizations report some area of skills gaps in data and analytics. Advanced analytic skills are at the top of the list with 44 percent reporting predictive, prescriptive and machine learning skills gaps exist in their business.
Alteryx introduces the newest version of the Alteryx Platform to democratize analytics and empower data native workers with new enterprise level innovations for seamless data efficiencies
“While data and analytics power the future, data literacy continues to be a challenge for organizations globally,” said Stewart Bond, Research Director, Data Integration and Data Intelligence Software, at IDC. “Data workers now expect more of their time to be spent on complex data science and application development instead of more basic prep and analytics tasks, but skills constraints and insufficient tools hinder progress. To succeed, organizations need to prioritize the democratization of data and analytics – putting the right tools in the right hands – with solutions that offer unified and automated data prep and analytic experiences.”
Goodbye data and analytic complexity, hello simplicity
Enterprises striving to work smarter by delivering value from data at the scale and speed today’s digital-first world demands are increasingly seeking to remove complexities associated with creating analytic outcomes. Underscoring the need for data and analytics simplicity and end-to-end analytics across a multiplicity of on and off-premises data sources, formats and qualities, the newest version of the Alteryx Platform (2021.4) simplifies delivering data-driven insights into the business. Key features and capability highlights of 2021.4 include:
- Create, centralize and share data connections across the enterprise: With Data Connection Manager (DCM), users will be able to accelerate scaling data and analytics across the business. Further simplifying processes associated with sharing and managing data connection access credentials to data sources. Now a single update to data connection information will be reflected for all workflows using that connection across the enterprise. Making it easy and simple to securely share, centralize and manage data connections.
- Streamline integration across the business: Enhanced Server APIs provide access to all the core Alteryx Server capabilities, enabling Server Admins to programmatically configure users, workflows, schedules, collections, connections, and credentials using an API. Opening the door for API automation as well as making it easier for teams to easily integrate Alteryx into broader IT processes and infrastructures.
- Unlock the value from a multiplicity of diverse unstructured datasets: The new Named Entity Recognition (NER) text mining tool provides automated document reading and text mining at scale, unlocking value from data embedded in image documents like PDFs or pictures, regardless of length or template format. Enabling organizations to fully operationalize data extraction from documents in automated analytic workflows.
- Connect to even more data sources: Enabling organizations to fully scale planning and analytics across the organization, a new Anaplan connector expands end-to-end analytics automation to combine a best-in-class business planning platform with a best-in-class data analytics platform. A new Automation Anywhere connector puts more automation flexibility and additional RPA capabilities directly into an Alteryx workflow, plus, new Google Drive and Outlook 365 connectors further simplify end-to-end analytics automation outcomes.
“Relying on spreadsheets for vital data work is like trying to power a rocket ship with a calculator. Businesses now need to reduce data and analytics complexity and uplevel the tools data workers are given,” said Suresh Vittal, chief product officer at Alteryx. “With 100,000 lifetimes wasted annually on analytics inefficiency, the time for a paradigm shift is now. The new and expanded capabilities of the Alteryx Analytic Automation Platform deliver a simplified interface and the improved analytic experience needed to seamlessly connect and scale analytics automation and RPA integration – both on-prem and in the cloud – to help flip the balance and re-optimize data science across the enterprise.”