The modern automotive industry is generating enormous volumes of manufacturing data every day. By analyzing this data, automakers can drive significant improvements in two critical areas: the initial production of their vehicles and the reliability of vehicles over their lifetimes.

Are you using your data to its fullest? This checklist will help you evaluate your existing automotive asset management strategy to ensure you’re getting the most out of your data.

In today’s digital business landscape, data is fragmented and scattered across various systems. Pulling all this data together is a significant challenge, and with businesses constantly implementing new data sources, cloud environments and other systems, integration complexities are multiplying quickly.

Enterprises have traditionally resorted to APIs to solve the point-to-point integration problems, but data scientists and data engineers have lost access to the raw tabular data and thus to analytics/BI. Data connectivity drivers (such as ODBC and JDBC connectors) effectively act as data APIs, enabling businesses to solve this unique challenge of exposing data for BI tools such as Tableau, Power BI, Qlik, Cognos, etc.

Chatbots have emerged as a great option for providing a 24/7 self-service solution to address a host of customer support requirements. As chatbot adoption has increased, various types have entered the market to address different requirements. This paper examines five key differences between transactional bots and knowledge bots and their fit for addressing customer self-service needs.