This Week in the DoT (Data of Things)

Every Friday, starting today, I will try to post some of what in my view were the relevant events during the week for the Data of Things, including news, videos, etc.

For today, I have a short list of influencers on Twitter — in no particular order — that you might want to follow for all data-related topics. I’m sure you will enjoy their tweets as much as I do:

Claudia Imhoff @Claudia_Imhoff
Merv Adrian @merv
Neil Raden @NeilRaden
Marcus Borba @marcusborba
Howard Dresner @howarddresner
Curt Monash @curtmonash
Cindi Howson @BIScorecard
Jim Harris @ocdqblog
Julie Hunt @juliebhunt

Of course, the list will grow in time. For now, enjoy following this group of great data experts.

Bon weekend!

Comments

Machine Learning and Cognitive Systems, Part 2: Big Data Analytics

In the first part of this series, I described a bit of what machine learning is and its potential to become a mainstream technology in the industry of enterprise software, and serve as the basis for many other advances in the incorporation of other technologies related to artificial intelligence and cognitive computing. I also mentioned briefly how machine language is becoming increasingly important for many companies in the business intelligence and analytics industry. In this post I will discuss further the importance that machine learning already has and can have in the analytics ecosystem, especially from a Big Data perspective. Machine learning in the context of BI and Big Data analytics Just as in the lab, and other areas, one of the reasons why machine learning became extremely important and useful in enterprise software is its potential to deal not just with huge amounts of data and extract knowledge from it—which can somehow be addressed with disciplines such as data

Next-generation Business Process Management (BPM)—Achieving Process Effectiveness, Pervasiveness, and Control

The range of what we think and do is limited by what we fail to notice. And because we fail to notice that we fail to notice there is little we can do to change until we notice how failing to notice shapes our thoughts and deeds. —R.D. Laing Amid the hype surrounding technology trends such as big data, cloud computing, or the Internet of Things, for a vast number of organizations, a quiet, persistent question remains unanswered: how do we ensure efficiency and control of our business operations? Business process efficiency and proficiency are essential ingredients for ensuring business growth and competitive advantage. Every day, organizations are discovering that their business process management (BPM) applications and practices are insufficient to take them to higher levels of effectiveness and control. Consumers of BPM technology are now pushing the limits of BPM practices, and BPM software providers are urging the technology forward. So what can we expect from the next

Teradata Open its Data Lake Management Strategy with Kylo: Literally

Still distilling good results from the acquisition of former consultancy company Think Big Analytics , Teradata , a powerhouse in the data management market took one step further to expand its data management stack and to make an interesting contribution to the open source community. Fully developed by the team at Think Big Analytics, in March of 2017 the company launched Kylo –a full data lake management solution– but with an interesting twist: as a contribution to the open source community. Offered as an open source project under the Apache 2.0 license Kylo is, according to Teradata, a new enterprise-ready data lake management platform that enables self-service data ingestion and preparation, as well the necessary functionality for managing metadata, governance and security. One appealing aspect of Kylo is it was developed over an eight year period, as the result of number of internal projects with Fortune 1000 customers which has enabled Teradata to incorporate several be

'D' of Things

Search This Blog