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At IKEA, the global home furnishings leader, data is more than an operational necessity—it’s a strategic asset. In a recent presentation at the SAPSA Impuls event in Stockholm , George Sandu, IKEA’s Master Data Leader, shared the company’s datatransformation story, offering valuable lessons for organizations navigating similar challenges.
As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor dataquality.
This is where we dispel an old “big data” notion (heard a decade ago) that was expressed like this: “we need our data to run at the speed of business.” Instead, what we really need is for our business to run at the speed of data. As you would guess, maintaining context relies on metadata.
Alerts and notifications play a crucial role in maintaining dataquality because they facilitate prompt and efficient responses to any dataquality issues that may arise within a dataset. This proactive approach helps mitigate the risk of making decisions based on inaccurate information.
Often, tech vendors act as an extended workforce, providing manpower and technological expertise for their client’s digitaltransformation journey. An IDC report estimated the global IT developer shortage will reach four million by 2025, leaving businesses struggling to accelerate digitaltransformation without the needed workforce.
Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value. Because data is one of the success elements of a digital agenda or digitaltransformation agenda.
cycle_end";') con.close() With this, as the data lands in the curated data lake (Amazon S3 in parquet format) in the producer account, the data science and AI teams gain instant access to the source data eliminating traditional delays in the data availability.
For years, IT and business leaders have been talking about breaking down the data silos that exist within their organizations. Given the importance of sharing information among diverse disciplines in the era of digitaltransformation, this concept is arguably as important as ever.
Data management has become a fundamental business concern, and especially for businesses that are going through a digitaltransformation. A survey from Tech Pro Research showed that 70 percent of organisations already have a digitaltransformation strategy or are developing one. Extraction, Transform, Load (ETL).
But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. Digitizing was our first stake at the table in our data journey,” he says. The offensive side?
What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure dataquality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.
Data & analytics represents a major opportunity to tackle these challenges. Indeed, many healthcare organizations today are embracing digitaltransformation and using data to enhance operations. In other words, they use data to heal more people and save more lives.
Use AI to improve data, and knowledge to improve AI The good news is AI is part of the solution, adds Siz. For example, gen AI can be used to generate synthetic data, and other forms of AI can be used to help analyze and improve dataquality.
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