DevOps on Snowflake – An Approach

Embedding a data platform into an application with the right tools is crucial. The cross-functional duo of Development and Operations (DevOps) on Snowflake helps characterize today's organization under shared networks, seamless workflow with automation, and instant feedback. In this whitepaper, we walk you through automated pipelines for Continuous Integration and Deployment along with - Streamlining DCM …

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Work Smart with Smart Apps

Smart Apps have evolved into essential business tools that are efficient and effective. The new apps are faster than previous generations, run faster, fail less frequently, and operate on a diverse set of devices and platforms. The nature of the latest apps drives the Smart Apps’ success as autonomous, intelligent and aware entities.

CI/CD and Automation of Data Pipelines

OverviewThis SpringML whitepaper demonstrates how to promote DevOps culture to secure communication and collaboration within a software team. With some best practices and key design, decisions learn how to establish an excellent Continuous Integration/Continuous Delivery standard practice for Google Cloud.

Deploying Chatbots to Production

The impact of chatbots across industries is rapidly expanding. Companies are utilizing these conversational AI tools to automate e-commerce, provide customer support, and even streamline internal business processes. Companies want more efficient ways to connect with their users and provide superior customer service, and users want an easier yet effective way to get products, services or information they are interested in from companies. Chatbots serve both these needs. This is why it is so imperative that chatbots are effectively designed and rigorously tested in order to increase business efficiency and meet customer satisfaction.

SAP HANA Integration to Google BigQuery

This SpringML Whitepaper demonstrates the ability to transfer the data from SAP HANA to Google BigQuery. The Whitepaper includes information on SAP HANA integration design and solution architecture, implementation, types of loading, and worker mechanism and Cloud Dataflow.

Building a Data Lake on BigQuery | Guidelines

Google’s BigQuery is an enterprise-grade cloud-native, serverless, fully managed, Petabyte scale, Data Warehouse as a Service. BigQuery is built on top of Dremel technology which has been in production internally in Google since 2006. Original Dremel papers were published in 2010 and Google Opened this technology as BigQuery to the public in 2011. This whitepaper provides guidelines and best practices for customers looking to leverage BigQuery to build a
Data Lake.

Analytics Workload Migration

OverviewAutomating data pipelines is at the heart of any analytics or machine learning project. SpringML experts will provide best practices and implementation support to build the end to end data pipeline in Google Cloud. We specialize in the following workload migrations: Enterprise Data Warehouse to Google Cloud. e.g Teradata to Google BigQuery On-premise Containerized applications to …

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AI Powered Order Taking Agent

OverviewIn today’s world, technology has touched so many aspects of our lives and businesses in an effort to save us time, energy, and generally make work and life easier. One experience that has remained virtually untouched by technological advancement is the fast food drive-thru and quick, convenient dining. With time and convenience at the forefront of …

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Next Gen Customer Service