vizually
Joined 10 years ago
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23
Submissions
32
Member since
Mar 28
Publisher of Data and Visualization Newsletter
View on Hacker NewsRecent submissions
Comment · 4 months ago
@greenpants, "Pi coding harness but containerized and sandboxed" care to address some specifics and/or reference implementation for this. may be a GITHub URL?
Comment · 4 years ago
In this issue, I cover -
• There are many databases and tools but where is the data platform?
• There are only three roles in data
• Data visualization color guide
• The Future of the (Modern) Data Stack
• Indexes in Postgres
Comment · 4 years ago
https://datawithdev.com/dc-03-data-job-trends-vc-money
In this third issue, following topics are covered.
The distribution of data jobs by primary technical skill (spoiler – Python & SQL win by a wide margin).
The rise of operational analytics.
Inspiring Tableau data visualizations
Big data, big money
Free learning resources on deep learning and a data engineering bootcamp
Comment · 5 years ago
This course was created after feedback from Reddit community and my own professional experience.
Despite content explosion, many data professionals could use a holistic look at data visualization, SQL, and Tableau.
Which is why I built this course.
If you are a student from a developing country, please DM and I will make it available for free to you.
Some of the videos are available on YouTube and more will be added. https://www.youtube.com/channel/UCC82PXmB2bhtejeSUXcJ_hw
Comment · 5 years ago
@NicoJuicy,
If you want to learn Cloud, definitely go ahead with Azure certifications.
If you are expecting to get hired because of certifications, that may be hoping for less than 5 percentile outcome.
Certifications do provide a defined goal and courses to get started.
Comment · 5 years ago
"Sunlight is the best disinfectant". I will bookmark it.
Comment · 5 years ago
If a start-up stage company is just getting started on their AI/ML journey has budget for 3 FTE people. The company already has traditional ETL/BI expertise and a "DWH". Who would you hire (data scientist, ML engineer, Dat Engineer) and how would you allocate the division of responsibilities?
Comment · 5 years ago
1. Depending on your application, the end users can be from different target market/background. If that will be the case with your app, list down the top X markets and create a specific landing page which "talks" the language of the target market.
2. Cold-outreach, Find your ideal target customers on LinkedIn/Twitter, google them, message/email them on social media (lead finding tools) and ask for help. Be willing to offer to pay them for 10-15 minutes of their time. At least a few will help without asking for money.
3. Assuming what you are selling is described on a landing page (doesn't have to be), you can do a user test by asking questions to consumers using survey tools) the goal is find out if users understand what you are trying to sell (clarity of message, trustworthiness)
You can use tools like Survey Monkey, Google Surveys, even Facebook ads.
here are a couple of examples of a purpose-built tool for feedback called ninjafeedback:
Comment · 5 years ago
also, looked at Snowflake's most recent quarterly results. They spent over $1.7 million/day in sales & marketing.