Understanding Enterprise Customer Engagement with the Modern Data Stack
Companies with B2C & B2B channels have unique challenges with intelligence and automation, best served by the Modern Data Stack.
Companies with B2C & B2B channels have unique challenges with intelligence and automation, best served by the Modern Data Stack.
This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection. The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization.
Enterprise data warehouse platform owners face a number of common challenges. In this article, we look at seven challenges, explore the impacts to platform and business owners and highlight how a modern data warehouse can address them.
Many organizations are working to become more data-driven – increasing data use and leveraging data insights to improve decision-making, solve their most challenging problems and improve revenue and profitability. A February 2020 IDC survey showed a direct correlation between quality decision-making and strong data-to-insight capabilities; 57 percent of organizations with the best data analytics pipelines received the highest decision-making score.
Use these five strategies to align key resources and ensure that insights guide your decision-making.
Data Scientists can drive innovation and growth, but you need to put in place the right foundation to fully unlock business value.