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Shaping the future: OMRON’s data-driven journey with AWS

AWS Machine Learning Blog

In their Shaping the Future 2030 (SF2030) strategic plan, OMRON aims to address diverse social issues, drive sustainable business growth, transform business models and capabilities, and accelerate digital transformation. Xinyi Zhou is a Data Engineer at Omron Europe, bringing her expertise to the ODAP team led by Emrah Kaya.

AWS 85
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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

The market for data warehouses is booming. billion by 2030. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes.

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Ways Big Data Creates a Better Customer Experience In Fintech

Smart Data Collective

billion on financial analytics by 2030. And Big Data is one such excellent opportunity ! Big Data is the collection and processing of huge volumes of different data types, which financial institutions use to gain insights into their business processes and make key company decisions.

Big Data 145
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The Role of RTOS in the Future of Big Data Processing

ODSC - Open Data Science

It is the preferred operating system for data processing heavy operations for many reasons (more on this below). Around 70 percent of embedded systems use this OS and the RTOS market is expected to grow by 23 percent CAGR within the 2023–2030 forecast period, reaching a market value of over $2.5 You can connect with him on LinkedIn.

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Discover the Most Important Fundamentals of Data Engineering

Pickl AI

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. They are crucial in ensuring data is readily available for analysis and reporting.

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ML Collaboration: Best Practices From 4 ML Teams

The MLOps Blog

As per a report by McKinsey , AI has the potential to contribute USD 13 trillion to the global economy by 2030. Union of business and data teams The success of ML projects lies in the strong collaboration between the data team and the business team.

ML 78
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Why Lean Data Management Is Vital for Agile Companies

Pickl AI

Focusing only on what truly matters reduces data clutter, enhances decision-making, and improves the speed at which actionable insights are generated. Streamlined Data Pipelines Efficient data pipelines form the backbone of lean data management. billion by 2030, at a CAGR of 13%.