Consistency is one of the most critical elements of accelerating API development as organizations try to meet increased demand, quality expectations, and regulatory requirements. Without a consistent API design to developers, there is no guarantee that the final result will match the intended purpose or the application depending on the API can function properly.
E-commerce is growing globally, forecasts for 2020 promise it to reach over 4 trillion USD and over 4.2 billion USD for retail e-commerce. We are approaching a very special season for online retail business owners: Black Friday, Cyber Monday and preparing for the holiday season. Every team behind an e-commerce business is planning big for this time. Every online store will try to attract as much traffic as possible. Are you planning to do the same?
As more and more companies are embedding AI projects into their systems, attracted by the promise of efficiencies and competitive advantages, data science teams are feeling the growing pains of a relatively immature practice without widespread established and repeatable norms.
Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to Microsoft HDInsight (also powered by Apache Hive-LLAP) on Azure using the TPC-DS 2.9 benchmark.
The CDO role has been rapidly evolving over the past few years – from governance leader to data science and AI expert to digital transformation guru. And, with this change, has come a shift from a back-office focus to a focus on achieving measurable results required by the C-suite.
When evaluating your approach to analytics and BI, a common comparison is Qlik vs. Tableau. Consistently, when we have that conversation, there are some sharp distinctions that come to the fore in terms of capabilities, vision and cost.
Let's talk media buying in the data age.
In 2018, Kong was first positioned onto the Gartner Magic Quadrant for Full Lifecycle API Management Market as a Visionary. This in itself was a very impressive feat given that Kong was started as an open source project just three years before that. I believe Kong’s progress on the Magic Quadrant in this short span of time speaks to how we have aligned Kong’s solutions to our customers’ most challenging problems.
In 20.1, Appian introduced Intelligent Document Processing or IDP. IDP lets Appian users leverage artificial intelligence to transform unstructured data from their business documents into structured data. Many business documents such as invoices, POs, loan applications, insurance claims, etc., include forms and/or check boxes. To support such use cases 20.3 now includes the ability to recognize and extract table and checkbox data from documents.
