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What Facebook Ad objective should you choose for your ad? Get advice from 60 marketing experts from agencies and small businesses.

While it is a little dated, one amusing example that has been the source of countless internet memes is the famous, “is this a chihuahua or a muffin?” classification problem. Figure 01: Is this a chihuahua or a muffin? In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin.

The value of healthy data is obvious. But how do you build that practice in your own business? The difference between people who live a healthy lifestyle and those who don’t isn’t whether they know how to be healthier — it’s whether or not they prioritize diet, sleep, and exercise in their daily life. The same is true for your data: if you don’t have the infrastructure that supports your customer 360 initiatives , those initiatives become moot.

Amazon Redshift says it executes data operations ten times faster than other enterprise data warehouses because of a hardware-accelerated cache called Advanced Query Accelerator (AQUAD). It also claims three times better price-performance than other similar technologies. Statements like these are what make Redshift an attractive option for companies that want to push data into a warehouse for analytics.

Digital technology promises transformative results. Yet, it’s not uncommon to encounter potholes and speed bumps along the way. One area that frequently trips up businesses is putting data into action. It can be extraordinarily difficult to take advantage of the right data at exactly the right time — in real time — to drive decision-making. For SAP customers wanting to maximize the value of their data, Google Cloud offers a number of capabilities.

Analysis-ready data models are built using sequences of transformations. Here's an example using Fivetran’s data model for Salesforce.

Kafka is a ubiquitous component of a modern data platform. It has acted as the buffer, landing zone, and pipeline to integrate your data to drive analytics, or maybe surface after a few hops to a business service. More recently, though, it has become the backbone for new digital services with consumer-facing applications that process live off the stream. As such, Kafka is being adopted by dozens, (if not hundreds) of software and data engineering teams in your organization.

Learn how 40 ecommerce pros use ecommerce analytics to optimize the performance of their online store and grow online sales.