Our journey in Talend Job Design Patterns & Best Practices is reaching an exciting juncture. My humble endeavor at providing useful content has taken on a life of its own. The continued success of the previous blogs in this series (please read Part 1,
Big Data Will Transform Every Element of the Healthcare Supply Chain
The entire healthcare supply chain has been being digitized for the last several years. We’ve already witnessed the use of big data to improve not only patient care, but also payer-provider systems, reducing wasted overhead, predict epidemics, cure diseases, improve the quality of life and avoid preventable deaths. Combine this with the mass adoption of edge technologies to improve patient care and wellbeing such as wearables, mobile imaging devices, mobile health apps, etc.
As we all prepare for the New Year, what are the top priorities on your agenda for 2017? Are data lakes part of it? Are you looking for ways to do it right? Then we might be able to help you go through the holiday break with some food for thought.
The use of statistics in business can be traced back hundreds of years. As early as 744 AD, statistics were used by Gerald of Wales to complete the first population census of Wales (1). It wasn’t long before merchants realized that statistics could be used to measure and quantify trade. The first record of this was in Florence. It was recorded in Giovanni Villani’s “Nuova Cronica”, in 1346 (1). Moreover, statistical methods were further adopted to help drive quality and in doing so helped contribute to the advancement of statistics
Did you know that a single organ donor can save up to 8 lives? The United Network for Organ Sharing (UNOS) is a private, non-profit organization that manages the United States’ national organ transplant system under contract with the federal government. On average, 85 people receive transplants every day, but another 22 people die each day while waiting for an organ transplant due to the lack of donors.
This blog is the first in a series of three looking at Data Matching and how this can be done within the Talend toolset. This first blog will look at the theory behind Data Matching, what is it and how it works. The second blog will look at the use of the Talend toolset for actually doing Data Matching. Finally, the last blog in the series will look at how you can tune the Data Matching algorithms to achieve the best possible Data Matching results.
This article aims to explain to IT and data professionals how to satisfy users' expectations about data access management while ensuring data control and data security. It provides advice for how to stimulate the use of governed, self-service data preparation.
According to Jacob Morgan, “Anything that can be connected, will be connected.” At one time, the terms cloud and big data were regarded as just ‘hype’, but now we’ve all witnessed the dramatic impact both of these key technologies have had on businesses across every industry around the globe. Now people are beginning to ask if the same is true of IoT—is this all just hype?
Last year, Talend introduced its annual Data Masters awards program, which recognizes companies that have dramatically transformed their businesses through [1innovative use of big data and cloud integration technologies.
Where’s a Russian Linesman When You Need One? Talend Scores Highest Position in Visionaries Quadrant for Data Quality
As some might recall, in the 1966 World Cup, Sir Geoff Hurst, a former English international football (A.K.A. ‘soccer’) player, scored a controversial goal during England’s World Cup final match against West Germany at Wembley Stadium that helped his team secure a 4–2 victory. For many the ball hadn’t crossed the goal line and therefore wasn’t a score; however, the Russian linesman saw things differently and ruled the goal ‘Good.'
Talend ran an online survey asking consumers in Singapore a series of questions related to data usage and privacy. The results provide some good insight into how big data impacts consumers’ lives in the region as well as their sometimes conflicted views on information sharing and confidentiality.
Yesterday at Amazon re:Invent, Werner Vogels, Amazon’s Chief Technology Officer outlined a vision for a modern data architecture that spans data ingestion, lifecycle management, data governance, orchestration and job scheduling. This vision included the announcement of Amazon Glue.
Everyone is talking about artificial intelligence (AI) and machine learning these days. This is not just of strategic relevance for companies the likes of Google, Apple, Amazon, Facebook or Salesforce.com. AI is now a term that all companies should be familiarizing themselves with (if they’re not already) because it will have a profound impact on their business in the near future.