IOT CATEGORIES
MOST POPULAR TAGS

To be or not to be a Data Hoarder

To be or not to be a Data Hoarder

IoT Big Data Management, Storage and Hoarding

Episode 22

How much IoT data should you keep? It’s not clear. The more data you keep, the more data transmission and storage costs you’ll incur. However thinning out your data store means throwing away potential future insights, potential answers to future questions and potential new information products to expand your business – all value generators unique to IoT products. In this episode of the IoT Business Show I speak with Steve Stover about balancing the costs and the technology approaches to maximize your Internet of Things data value.

In this episode of the IoT Business Show I speak with Steve Stover about balancing the costs and the technology approaches to maximize your Internet of Things data value.

Steve is the Sr. Director of Product Management with Predixion Software. Over the last 20 years, Steve has provided product and technology leadership to deliver Big Data and Analytics solutions at companies including Dell and Teradata.

Technology provides some of the answers. As computing platforms are becoming more robust, so too is the migration of analytics from the cloud to the cloud edge to the fog (in IT gateways) and even all the way down to the end node or thing. All choices have different costs and keep open different options for monetizing your data in the future. As always these decisions have to be driven from the top down into what I call the BIRD – the business information requirements document. Listen to this episode to appreciate all the variables at play in this complex question – to be or not to be a data hoarder.

Here’s What We’ll Cover in this Episode

  • Looking into the past, present and future with analytics
  • Building your analytics infrastructure (on prem) versus renting it (in the cloud)
  • How old school application connectors are giving way to new school REST-based APIs
  • How ETL (extract, transform and load) is still alive and well
  • Different homes for today’s analytics
  • How to avoid data “blind spots”
  • The four main costs associated with analytics
  • The two main analytics business models
  • The value of edge-based analytics

DOWNLOAD TRANSCRIPT

Mentioned in this Episode and Other Useful Links

Support this Podcast

If you have been enjoying this podcast, there are a few ways you can support it:

  1. Share it on social by clicking on the widget on the left or bottom of the page.
  2. Click here to open iTunes and leave a one-click review or write your thoughts.
  3. Leave a donation via PayPal by clicking on the button below.

Ways to Subscribe to the IoT Business Show

Like what you hear?  Subscribe to get each episode delivered to your device via iTunes, Stitcher Radio or RSS (non-iTunes feed).

Have an opinion? Join the discussion in our LinkedIn group

When, if ever, do you see edge-based analytics making most sense?

Related Posts