Big Data Analytics stands apart from conventional data processing in its fundamental nature. In the realm of Big Data, there are two prominent architectural concepts that perplex companies embarking on the construction or restructuring of their Big Data platform: Lambda architecture or Kappa architecture.   Read more here: Lambda vs Kappa Architecture for Data Cloud Platforms   The post Kappa vs Lambda Architecture appeared first on Data Science Blog (English only ..read more

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. The database for Process Mining is also establishing itself as an important hub for Data Science and AI applications, as process traces are very granular and informative about what is really going on in the business processes. The trend towards powerful in-house cloud platforms for data and analysis ensures that large volumes of data can increasingly be stored and used flexibly. This aspect can be applie ..read more

Companies use Business Intelligence (BI), Data Science, and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. BI provides real-time data analysis and performance monitoring, while Data Science enables a deep dive into dependencies in data with data mining and automates decision making with predictive analytics and personalized customer experiences. Process Mining offers process transparency, compliance insights, and process optimization. The integration of these technologies helps companies harness data for growth and effic ..read more

Big Data Analytics stands apart from conventional data processing in its fundamental nature. In the realm of Big Data, there are two prominent architectural concepts that perplex companies embarking on the construction or restructuring of their Big Data platform: Lambda architecture or Kappa architecture. Thus, it is crucial for such companies to contemplate and decide which architectural approach best aligns with their goals. Lambda – Architecture Introduced in 2011 during the peak of Big Data’s prominence, the Lambda architecture remains a significant presence in the field. Despite being the ..read more

Data analytics in HR can help businesses make informed decisions for hiring, promotion and digital transformation. While human resources is typically considered a “soft” discipline, information can reveal invaluable insights that help professionals deliver tangible improvements. What role does data play in HR analytics and success? The Value of Data in HR Data is crucial for the success of HR analytics tools. It increases visibility into business processes and the employee experience. The information analytics reveals allows decisions to be based on proven facts rather than subjective assumpti ..read more

Data-driven approaches have become standard across many industries, but some still need to catch up for using Big Data. Health care has slowly embraced digital transformation and data analytics, but senior living facilities have room to improve under that umbrella. If more long-term care (LTC) organizations adopted data initiatives, they could significantly improve their patients’ standards of living. Almost a quarter of LTC providers report having “very little” ability to access and share patient data electronically. Nearly a third still rely on email or fax for these processes, and 18% are e ..read more

AI is here and is not going away. The value of the AI market is only set to increase, with it estimated to surpass a value of $89 billion a year by 2025, and an important part of this market will be AI that powers cloud computing. AI and cloud computing are already impacting our lives, with the prevalence of digital assistants like Alexa, Google Home, and Siri, and cloud computing is not only a cost-effective data storage and processes solution but a vital part of the adoption of AI. Combining AI with cloud computing is bringing about a revolution in cloud computing systems, enabling massive n ..read more

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves. The increasing number of papers on deep learning demonstrate that researches on AI have developed rapidly recently. If architectures of neural networks and supervised learning are all you know about deep learning, you will be overwhelmed by complications of topics studied these days, for example generative models, maki ..read more

In the era of Industry 4.0, linking data from MES (Manufacturing Execution System) with that from ERP, CRM and PLM systems plays an important role in creating integrated monitoring and control of business processes. ERP (Enterprise Resource Planning) systems contain information about finance, supplier management, human resources and other operational processes, while CRM (Customer Relationship Management) systems provide data about customer relationships, marketing and sales activities. PLM (Product Lifecycle Management) systems contain information about products, development, design and engin ..read more

Data is the lifeblood of an organization and businesses that fail to embrace this fundamental concept risk losing future business opportunities or the company itself. The value of business and consumer data hasn’t been lost on cybercriminals, which is why phishing attacks and other data security threats have been more rampant through the years. As data technology becomes more advanced, reliance on data becomes a more significant opportunity for exploitation as even the most advanced data systems have their vulnerabilities. Businesses collect and process large amounts of data from several sourc ..read more