From May 21st to May 24th, Amalgam Insights attended Informatica World. Both my colleague Tom Petrocelli and I were able to attend and gain insights on present and future of Informatica. Based on discussions with Informatica executives, customers, and partners, I gathered the following takeaways.
Informatica made a number of announcements that fit well into the new era of Machine Learning that is driving enterprise IT in 2018. Tactically, Informatica’s announcement of providing its Intelligent Cloud Services, its Integration Platform as a Service offering, natively on Azure represents a deeper partnership with Microsoft. Informatica’s data integration, synchronization, and migration services go hand-in-hand with Microsoft’s strategic goal of getting more data into the Azure cloud and shifting the data gravity of the cloud. Amalgam believes that this integration will also help increase the value of Azure Machine Learning Studio, which now will have more access to enterprise data.
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Last week, I attended Strata Data Conference at the Javitz Center in New York City to catch up with a wide variety of data science and machine learning users, enablers, and thought leaders. In the process, I had the opportunity to listen to some fantastic keynotes and to chat with 30+ companies looking for solutions, 30+ vendors presenting at the show, and attend with a number of luminary industry analysts and thought leaders including Ovum’s Tony Baer, EMA’s John Myers, Aberdeen Group’s Mike Lock, and Hurwitz & Associates’ Judith Hurwitz.
From this whirwind tour of executives, I took a lot of takeaways from the keynotes and vendors that I can share and from end users that I unfortunately have to keep confidential. To give you an idea of what an industry analyst notes, following are a short summary of takeaways I took from the keynotes and from each vendor that I spoke to:
Keynotes: The key themes that really got my attention is the idea that AI requires ethics, brought up by Joanna Bryson, and that all data is biased, which danah boyd discussed. This idea that data and machine learning have their own weaknesses that require human intervention, training, and guidance is incredibly important. Over the past decade, technologists have put their trust in Big Data and the idea that data will provide answers, only to find that a naive and “unbiased” analysis of data has its own biases. Context and human perspective are inherent to translating data into value: this does not change just because our analytic and data training tools are increasingly nuanced and intelligent in nature.
Behind the hype of data science, Big Data, analytic modeling, robotic process automation, DevOps, DataOps, and artifical intelligence is this fundamental need to understand that data, algorithms, and technology all have inherent biases as the following tweet shows:
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New Informatica Brand for New Informatica Aspirations
Amalgam Insights (AI) recently attended Informatica World 2017, where executives, partners, and customers provided backing for Informatica’s ability to support “The Disruptive Power of Data,” (an Informatica-trademarked phrase) as well as its positioning as the Enterprise Cloud Data Management leader.
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