Moesif had the privilege of picking the brain of the expert who literally wrote the book on API Product Management. In a wide-ranging discussion with Dr. Amancio Bouza we found out what you should really care about as an API product manager, and it’s not what you may think (hint: see the title). We also cover pricing your API, how to become a better product manager and what books should be on your nightstand.
Logs are an important part of your application and logging shouldn’t be one of the last things you think of. You should configure your log system, formatter, and style as soon as you start the development of your app. Also, do your best to document the process and share how it works with the rest of your team. In this article, we’re going to demonstrate how logs work in Elixir. We’ll jump into Elixir’s Logger module, which brings a lot of power to logging features.
The COVID-19 global pandemic has added new urgency to the quest for digital transformation. The pandemic disrupted business processes and displaced and disconnected people. Organizations across the globe witnessed first-hand that the speed with which they could get new automations and applications in place could literally make or break the company. The world quickly learned what some industry leaders already knew: the ability to develop an application and quickly bring it to market is crucial.
Tapping into more compute power is the next frontier of data science. Data scientists need it to complete increasingly complex machine learning (ML) and deep learning (DL) tasks without it taking forever. Otherwise, faced with a long wait for compute jobs to finish, data scientists give in to the temptation to test smaller datasets or run fewer iterations in order to produce results more quickly.
Much has been written on the growth of machine learning and its impact on almost every industry. As businesses continue to evolve and digitally transform, it’s become an imperative for businesses to include AI and ML in their strategic plans in order to remain competitive. In Competing in the Age of AI, Harvard professors Marco Iansiti and Karim R. Lakhani illustrate how this can be confounding for CEOs, especially in the face of AI-powered competition.
Modern business applications leverage Machine Learning (ML) and Deep Learning (DL) models to analyze real-world and large-scale data, to predict or to react intelligently to events. Unlike data analysis for research purposes, models deployed in production are required to handle data at scale and often in real-time, and must provide accurate results and predictions for end-users.
Data science has come a long way, and it has changed organizations across industries profoundly. In fact, over the last few years, data science has been applied not for the sake of gathering and analyzing data but to solve some of the most pertinent business problems afflicting commercial enterprises.
We’re delighted to announce the release of the Iguazio Data Science Platform version 2.8. The new version takes another leap forward in solving the operational challenge of deploying machine and deep learning applications in real business environments. It provides a robust set of tools to streamline MLOps and a new set of features that address diverse MLOps challenges.
Recently, my colleague published a blog build on your investment by Migrating or Upgrading to CDP Data Center, which articulates great CDP Private Cloud Base features. Existing CDH and HDP customers can immediately benefit from this new functionality. This blog focuses on the process to accelerate your CDP journey to CDP Private Cloud Base for both professional services engagements and self-service upgrades.
Since Snowflake announced general availability on Azure in November 2018, increasing numbers of customers are deploying their Snowflake accounts on Azure, and with this, more customers are using Power BI as the data visualization and analysis layer. As a result of these trends, customers want to understand the best practices for a successful deployment of Power BI with Snowflake.
