Category: Application Integration

As enterprises move from running ad hoc machine learning (ML) models to using AI/ML to transform their business at scale, the adoption of ML Operations (MLOps) becomes inevitable. As shown in the following figure, the ML lifecycle begins with framing a business problem as an ML use case followed by a series of phases, including […]

In a previous post, we talked about analyzing and tagging assets stored in Veeva Vault PromoMats using Amazon AI services and the Veeva Vault Platform’s APIs. In this post, we explore how to use Amazon AppFlow, a fully managed integration service that enables you to securely transfer data from software as a service (SaaS) applications […]

Having an environment capable of delivering Amazon SageMaker notebook instances quickly allows data scientists and business analysts to efficiently respond to organizational needs. Data is the lifeblood of an organization, and analyzing that data efficiently provides useful insights for businesses. A common issue that organizations encounter is creating an automated pattern that enables development teams […]

This is a guest post written by Gergely Kadi, Senior Systems Engineer and Martin Petraschek-Stummer, Senior Data Engineer at TourRadar. TourRadar is a travel marketplace to connect people to life-enriching travel experiences. When it was launched, TourRadar only offered tours and content in English. As the company grew, we saw an opportunity to expand our […]

Data scientists can spend up to 80% of their time preparing data for machine learning (ML) projects. This preparation process is largely undifferentiated and tedious work, and can involve multiple programming APIs and custom libraries. Announced at AWS re:Invent 2020, Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for […]

Organizations of all sizes and across all industries gather and analyze metrics or key performance indicators (KPIs) to help their businesses run effectively and efficiently. Operational metrics are used to evaluate performance, compare results, and track relevant data to improve business outcomes. For example, you can use operational metrics to determine application performance (the average […]

The ability to scale machine learning operations (MLOps) at an enterprise is quickly becoming a competitive advantage in the modern economy. When firms started dabbling in ML, only the highest priority use cases were the focus. Businesses are now demanding more from ML practitioners: more intelligent features, delivered faster, and continually maintained over time. An […]

Data is proliferating inside the enterprise and employees are using more applications than ever before to get their jobs done, in fact according to Okta Inc., the number of software apps deployed by large firms across all industries world-wide has increased 68%, reaching an average of 129 apps per company. As employees continue to self-serve […]

January 2022 – HiConversion is now Obviyo. We have updated this blog to reflect the new company name. You can read more about the name change on Obviyo’s blog. This is a guest post by Jeff McKelvey, Principal Development Lead at Obviyo. The team at Obviyo has collaborated closely with James Jory, Applied AI Services […]