Business Intelligence In The Palm Of Your Hand With Zing Data
Publisher |
Tobias Macey
Media Type |
audio
Podknife tags |
Data Science
Interview
Technology
Categories Via RSS |
Technology
Publication Date |
Dec 05, 2022
Episode Duration |
00:46:46

Summary

Business intelligence is the foremost application of data in organizations of all sizes. The typical conception of how it is accessed is through a web or desktop application running on a powerful laptop. Zing Data is building a mobile native platform for business intelligence. This opens the door for busy employees to access and analyze their company information away from their desk, but it has the more powerful effect of bringing first-class support to companies operating in mobile-first economies. In this episode Sabin Thomas shares his experiences building the platform and the interesting ways that it is being used.

Announcements

  • Hello and welcome to the Data Engineering Podcast, the show about modern data management
  • When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/linode today and get a $100 credit to launch a database, create a Kubernetes cluster, or take advantage of all of their other services. And don’t forget to thank them for their continued support of this show!
  • Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Go to dataengineeringpodcast.com/atlan today to learn more about how Atlan’s active metadata platform is helping pioneering data teams like Postman, Plaid, WeWork & Unilever achieve extraordinary things with metadata and escape the chaos.
  • Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day. Especially once they realize 90% of all major data sources like Google Analytics, Salesforce, Adwords, Facebook, Spreadsheets, etc., are already available as plug-and-play connectors with reliable, intuitive SaaS solutions. Hevo Data is a highly reliable and intuitive data pipeline platform used by data engineers from 40+ countries to set up and run low-latency ELT pipelines with zero maintenance. Boasting more than 150 out-of-the-box connectors that can be set up in minutes, Hevo also allows you to monitor and control your pipelines. You get: real-time data flow visibility, fail-safe mechanisms, and alerts if anything breaks; preload transformations and auto-schema mapping precisely control how data lands in your destination; models and workflows to transform data for analytics; and reverse-ETL capability to move the transformed data back to your business software to inspire timely action. All of this, plus its transparent pricing and 24*7 live support, makes it consistently voted by users as the Leader in the Data Pipeline category on review platforms like G2. Go to dataengineeringpodcast.com/hevodata and sign up for a free 14-day trial that also comes with 24×7 support.
  • Struggling with broken pipelines? Stale dashboards? Missing data? If this resonates with you, you’re not alone. Data engineers struggling with unreliable data need look no further than Monte Carlo, the leading end-to-end Data Observability Platform! Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines. Monte Carlo monitors and alerts for data issues across your data warehouses, data lakes, dbt models, Airflow jobs, and business intelligence tools, reducing time to detection and resolution from weeks to just minutes. Monte Carlo also gives you a holistic picture of data health with automatic, end-to-end lineage from ingestion to the BI layer directly out of the box. Start trusting your data with Monte Carlo today! Visit dataengineeringpodcast.com/montecarlo to learn more.
  • Your host is Tobias Macey and today I’m interviewing Sabin Thomas about Zing Data, a mobile-friendly business intelligence platform

Interview

  • Introduction
  • How did you get involved in the area of data management?
  • Can you describe what Zing Data is and the story behind it?
  • Why is mobile access to a business intelligence system important?
    • What does it mean for a business intelligence system to be mobile friendly? (e.g. just looking at charts vs. creating reports, etc.)
  • What are the interaction patterns that don’t translate well to mobile from web or desktop BI systems?
    • What are the new interaction patterns that are enabled by the mobile experience?
  • What are the capabilities that a native app can provide which would be clunky or impossible as a web app on a mobile device?
  • Who are the personas that benefit from a product like Zing Data?
  • Can you describe how the platform (backend and app) are implemented?
    • How have the design and goals of the system changed/evolved since you started working on it?
  • Can you describe a typical workflow for a team that uses Zing?
    • Is it typically the sole/primary BI system, or is it more of an augmentation?
  • What are the most interesting, innovative, or unexpected ways that you have seen Zing used?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on Zing?
  • When is Zing the wrong choice?
  • What do you have planned for the future of Zing Data?

Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

  • Thank you for listening! Don’t forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
  • Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
  • If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com) with your story.
  • To help other people find the show please leave a review on Apple Podcasts and tell your friends and co-workers

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Summary

Business intelligence is the foremost application of data in organizations of all sizes. The typical conception of how it is accessed is through a web or desktop application running on a powerful laptop. Zing Data is building a mobile native platform for business intelligence. This opens the door for busy employees to access and analyze their company information away from their desk, but it has the more powerful effect of bringing first-class support to companies operating in mobile-first economies. In this episode Sabin Thomas shares his experiences building the platform and the interesting ways that it is being used.

Announcements

  • Hello and welcome to the Data Engineering Podcast, the show about modern data management
  • When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/linode today and get a $100 credit to launch a database, create a Kubernetes cluster, or take advantage of all of their other services. And don’t forget to thank them for their continued support of this show!
  • Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Go to dataengineeringpodcast.com/atlan today to learn more about how Atlan’s active metadata platform is helping pioneering data teams like Postman, Plaid, WeWork & Unilever achieve extraordinary things with metadata and escape the chaos.
  • Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day. Especially once they realize 90% of all major data sources like Google Analytics, Salesforce, Adwords, Facebook, Spreadsheets, etc., are already available as plug-and-play connectors with reliable, intuitive SaaS solutions. Hevo Data is a highly reliable and intuitive data pipeline platform used by data engineers from 40+ countries to set up and run low-latency ELT pipelines with zero maintenance. Boasting more than 150 out-of-the-box connectors that can be set up in minutes, Hevo also allows you to monitor and control your pipelines. You get: real-time data flow visibility, fail-safe mechanisms, and alerts if anything breaks; preload transformations and auto-schema mapping precisely control how data lands in your destination; models and workflows to transform data for analytics; and reverse-ETL capability to move the transformed data back to your business software to inspire timely action. All of this, plus its transparent pricing and 24*7 live support, makes it consistently voted by users as the Leader in the Data Pipeline category on review platforms like G2. Go to dataengineeringpodcast.com/hevodata and sign up for a free 14-day trial that also comes with 24×7 support.
  • Struggling with broken pipelines? Stale dashboards? Missing data? If this resonates with you, you’re not alone. Data engineers struggling with unreliable data need look no further than Monte Carlo, the leading end-to-end Data Observability Platform! Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines. Monte Carlo monitors and alerts for data issues across your data warehouses, data lakes, dbt models, Airflow jobs, and business intelligence tools, reducing time to detection and resolution from weeks to just minutes. Monte Carlo also gives you a holistic picture of data health with automatic, end-to-end lineage from ingestion to the BI layer directly out of the box. Start trusting your data with Monte Carlo today! Visit dataengineeringpodcast.com/montecarlo to learn more.
  • Your host is Tobias Macey and today I’m interviewing Sabin Thomas about Zing Data, a mobile-friendly business intelligence platform

Interview

  • Introduction
  • How did you get involved in the area of data management?
  • Can you describe what Zing Data is and the story behind it?
  • Why is mobile access to a business intelligence system important?
    • What does it mean for a business intelligence system to be mobile friendly? (e.g. just looking at charts vs. creating reports, etc.)
  • What are the interaction patterns that don’t translate well to mobile from web or desktop BI systems?
    • What are the new interaction patterns that are enabled by the mobile experience?
  • What are the capabilities that a native app can provide which would be clunky or impossible as a web app on a mobile device?
  • Who are the personas that benefit from a product like Zing Data?
  • Can you describe how the platform (backend and app) are implemented?
    • How have the design and goals of the system changed/evolved since you started working on it?
  • Can you describe a typical workflow for a team that uses Zing?
    • Is it typically the sole/primary BI system, or is it more of an augmentation?
  • What are the most interesting, innovative, or unexpected ways that you have seen Zing used?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on Zing?
  • When is Zing the wrong choice?
  • What do you have planned for the future of Zing Data?

Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

  • Thank you for listening! Don’t forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
  • Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
  • If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com) with your story.
  • To help other people find the show please leave a review on Apple Podcasts and tell your friends and co-workers

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Support Data Engineering Podcast

Summary

Business intelligence is the foremost application of data in organizations of all sizes. The typical conception of how it is accessed is through a web or desktop application running on a powerful laptop. Zing Data is building a mobile native platform for business intelligence. This opens the door for busy employees to access and analyze their company information away from their desk, but it has the more powerful effect of bringing first-class support to companies operating in mobile-first economies. In this episode Sabin Thomas shares his experiences building the platform and the interesting ways that it is being used.

Announcements

  • Hello and welcome to the Data Engineering Podcast, the show about modern data management
  • When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/linode today and get a $100 credit to launch a database, create a Kubernetes cluster, or take advantage of all of their other services. And don’t forget to thank them for their continued support of this show!
  • Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Go to dataengineeringpodcast.com/atlan today to learn more about how Atlan’s active metadata platform is helping pioneering data teams like Postman, Plaid, WeWork & Unilever achieve extraordinary things with metadata and escape the chaos.
  • Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day. Especially once they realize 90% of all major data sources like Google Analytics, Salesforce, Adwords, Facebook, Spreadsheets, etc., are already available as plug-and-play connectors with reliable, intuitive SaaS solutions. Hevo Data is a highly reliable and intuitive data pipeline platform used by data engineers from 40+ countries to set up and run low-latency ELT pipelines with zero maintenance. Boasting more than 150 out-of-the-box connectors that can be set up in minutes, Hevo also allows you to monitor and control your pipelines. You get: real-time data flow visibility, fail-safe mechanisms, and alerts if anything breaks; preload transformations and auto-schema mapping precisely control how data lands in your destination; models and workflows to transform data for analytics; and reverse-ETL capability to move the transformed data back to your business software to inspire timely action. All of this, plus its transparent pricing and 24*7 live support, makes it consistently voted by users as the Leader in the Data Pipeline category on review platforms like G2. Go to dataengineeringpodcast.com/hevodata and sign up for a free 14-day trial that also comes with 24×7 support.
  • Struggling with broken pipelines? Stale dashboards? Missing data? If this resonates with you, you’re not alone. Data engineers struggling with unreliable data need look no further than Monte Carlo, the leading end-to-end Data Observability Platform! Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines. Monte Carlo monitors and alerts for data issues across your data warehouses, data lakes, dbt models, Airflow jobs, and business intelligence tools, reducing time to detection and resolution from weeks to just minutes. Monte Carlo also gives you a holistic picture of data health with automatic, end-to-end lineage from ingestion to the BI layer directly out of the box. Start trusting your data with Monte Carlo today! Visit dataengineeringpodcast.com/montecarlo to learn more.
  • Your host is Tobias Macey and today I’m interviewing Sabin Thomas about Zing Data, a mobile-friendly business intelligence platform

Interview

  • Introduction
  • How did you get involved in the area of data management?
  • Can you describe what Zing Data is and the story behind it?
  • Why is mobile access to a business intelligence system important?
    • What does it mean for a business intelligence system to be mobile friendly? (e.g. just looking at charts vs. creating reports, etc.)
  • What are the interaction patterns that don’t translate well to mobile from web or desktop BI systems?
    • What are the new interaction patterns that are enabled by the mobile experience?
  • What are the capabilities that a native app can provide which would be clunky or impossible as a web app on a mobile device?
  • Who are the personas that benefit from a product like Zing Data?
  • Can you describe how the platform (backend and app) are implemented?
    • How have the design and goals of the system changed/evolved since you started working on it?
  • Can you describe a typical workflow for a team that uses Zing?
    • Is it typically the sole/primary BI system, or is it more of an augmentation?
  • What are the most interesting, innovative, or unexpected ways that you have seen Zing used?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on Zing?
  • When is Zing the wrong choice?
  • What do you have planned for the future of Zing Data?

Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

  • Thank you for listening! Don’t forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
  • Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
  • If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com) with your story.
  • To help other people find the show please leave a review on Apple Podcasts and tell your friends and co-workers

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Support Data Engineering Podcast

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