CTO & Co-founder @switchboardsoft. Building the platform that leading media companies use to unify data.
California, USA
Joined February 2009
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Energizing day for everyone at Switchboard Software - by partnering with GFT Ventures and Quest Ventures, we are step closer to our goal of helping all companies become more data- and AI-driven. I am personally looking forward to accelerating our next phase of product updates!
Exciting news from VentureBeat on our recent Series A led by GFT Ventures and Quest Venture Partners!
Congratulations to our Founders @jukaykwek and @doubleocherry and the entire Switchboard team 🎉
Stay tuned for more news (and more "new"s) to come..
lnkd.in/gvBHVsuQ
Visit events.switchboard-software.… to register for our fireside chat (Tue Oct 12 @ 9:30 PT). Ju-kay Kwek and I will join Ameen Kazerouni, Chief Data and Analytics Officer at Orangetheory Fitness, to discuss the role of data in driving marketing efficiency.
When managing data operations at scale, it's important to have access to metadata to make sure problems don't eat up valuable time. At minimum - access to business rule change logs, data volume, error rates. @JamesKobielus provides great examples of this:
tdwi.org/articles/2021/07/07…
Michael Manoochehri retweeted
We're delivering the #publisher industry's first integrated solution for CRM+OMS+Data Ops by joining forces with @switchboardsoft! bit.ly/3h0dZVe #BoostrCRM #BeDataStrong #partnership
Organizations are investing heavily in data science technologies, but these investments are putting immense pressure on data science teams. 81% of data engineers cited that "the need for data products was increasing at a faster rate than their team size."
aithority.com/technology/big…
"The first step in establishing a data lake is data ingestion. It is often considered a low priority task. The alarm rings when the volume & variety of data increase, leading to input maintenance and management issues."
newsanyway.com/2021/06/02/ho…
Mature data teams treat data validation as an essential Data Operations process which includes version control and auditability. This article provides a great summary of how teams at Amazon and Google approach data validation:
kdnuggets.com/2021/05/data-v…
Michael Manoochehri retweeted
Data ingestion, data versioning, data validation, and data pre-processing are imperative, not optional. This article discusses data validation, why it is important, its challenges, and more...
bit.ly/3fjAeEX
#datavalidation #bigdata #dataops #dataingestion #ML
Data Democracy: an organization should be built around data, not vice-versa. This article provides a great overview about what might be preventing your organization from using your data effectively.
cdotrends.com/story/15538/da…
As Gartner famously reported, over 60% (and probably closer to 80%) of data projects eventually fail. This article is a great summary of how to ensure data projects succeed. In my experience defining the "practical applications for your data" is paramount
enterprisersproject.com/arti…
It's a pleasure to welcome Doug Sykes to the @switchboardsoft team! Doug brings a wealth of data and visualization domain experience to support our customers' success. #customersuccess #data #bedatastrong switchboard-software.com/pos…
Great article by @timglomb via @HarvardBiz. The end of 3rd party cookies is a welcome correction to consumer privacy issues. Proud that @switchboardsoft helps leading brands build data assets that allow them to engage with consumers directly.
hbr.org/2021/04/say-goodbye-…
Michael Manoochehri retweeted
With the growing accumulation of structured, unstructured and semi-structured data in organizations - increasingly as big data applications are adopted - dark data denotes operational data that is left un-analyzed.
bit.ly/3sMaXaG
#bigdata #data #darkdata #dataops
Great read: This MIT @techreview post by @_KarenHao claims that "the 10 most cited AI data sets are riddled with label errors". Indeed, the inability to maintain data quality over time and at scale is a common concern for Machine Learning projects. technologyreview.com/2021/04…
The @infolabUK 's @lowers_ryan wrote an excellent blog post about how to think about Data Quality. Two quality processes that many teams overlook: historical logging of pipeline data and transparent access to version-controlled business rule definitions. theinformationlab.co.uk/2021…
Gartner's recent Magic Quadrant on Data Sci/ML: AI still "overhyped" but investments in data science and ML are resulting in more practical gains.
I agree: Orgs that are effectively investing in these technologies continue to differentiate themselves.
venturebeat.com/2021/03/14/g…
A fantastic #CHI paper from Google Research: Everyone wants to do the model work, not the data work.
"We need to move towards a proactive focus on data excellence—focusing on the practices, politics, and values of humans of the data pipeline." storage.googleapis.com/pub-t…