2020 was quite a year of innovation for Qlik analytics. We delivered key new augmented analytics capabilities with big updates to Insight Advisor, we integrated intelligent alerts fully into Qlik Sense in less than a year, we continued to expand our visualization capabilities to make it easier to showcase your data in exciting and compelling ways, and we made it even easier to execute analytics in the cloud.
The key differences between Amazon Kinesis and Kafka are: Introducing data streamers! These services validate and route messages from one application to another, managing workload and message queues effectively. The result? Users process messages through a centralized processor and handle large data streams more efficiently. Amazon Kinesis and Apache Kafka are two data stream services.
Mobile sales traffic is growing at an unprecedented rate. In retail and e-commerce, the only way to engage customers in the long-run is by creating intuitive, flawless, and enjoyable mobile shopping experiences that go beyond a single purchase.
One of the highly anticipated events every year is the keynote from Dr. Werner Vogels at the annual AWS Reinvent conference. As CTO of Amazon, Dr. Vogels has considerable influence on product and engineering innovation that directly impacts hundreds of millions of users and developers. Here are three takeaways from Dr. Vogels’ keynote this year.
Snowflake met with Mark Stange-Tregear, Vice President of Analytics for Rakuten Rewards, and Andrew Parry, Vice President of IT Application Development for Office Depot, at Data Cloud Summit 2020. The Data Cloud is unlocking new ways of delivering products and services to customers, managing supply chains, and collaborating globally. Rakuten Rewards and Office Depot are going “all- in” on the Snowflake Data Cloud to transform their businesses. Q. How does data affect your business?
There has been an e-commerce explosion this year as consumers seek safety and convenience from the comfort of their own homes using digital tools to purchase everything from durable hard goods to fashion accessories to daily living consumables like food perishables, cleaning products and even school supplies.
An old airport customer of mine (whilst I worked for another company) used to pop someone next to a busy runway with a stopwatch strapped round their neck. The unfortunate person had to manually log the time aircrafts spent on the runway to measure the runway occupancy. All very archaic. Even in those days.
There’s no doubt which programming language is winning the battle for global supremacy right now. JavaScript has powered past the 12 million developers mark, and 5 million of its loyal fans (some 40%) have come aboard within the last three years. Initially thought of as merely a Java spin-out, it is now used to power everything from machine learning libraries to space exploration robots. But to truly maximize the potential of JavaScript, developers have to implement an effective testing regime.
Building a multi-region or multi-cloud environment for your applications requires a lot of attention. In a typical deployment, you would have an API gateway running close to the several application runtimes. You should enhance your deployment to support different regions in a given cloud, or in an even more distributed and hybrid scenario, multiple services running across other public clouds and on-premise environments.
When it comes to machine learning (ML) in the enterprise, there are many misconceptions about what it actually takes to effectively employ machine learning models and scale AI use cases. When many businesses start their journey into ML and AI, it’s common to place a lot of energy and focus on the coding and data science algorithms themselves.
