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A practical framework for data quality is often been overlooked as businesses focus on immediate value, with increased revenues and decreased costs.With data becoming increasingly integrated with strategy and operations, the bottom-line impact of data quality is increasing. Relatively newer corporate functions like sales operations and revenue operations use data heavily and with increasing depth. The professionals in these functions are very intentional about how they want to use data to generate value, and the data has to be accurate, timely, complete, and reliable. They rely on the data to make business decisions. They design processes and automate systems that use this data. Data quality has become a priority. Despite the increasing awareness of data quality, challenges still get in the way of data quality initiatives:Resources are limited.It is challenging to show the impact of data quality actions. The data sources, flows, and uses are flourishing, making it more challenging to prioritize data quality efforts.This document will share our data quality framework for planning data quality actions, current state assessments, and prioritizing data quality initiatives.Before we dive deeper, we want to remind the reader that our scope is the cloud data warehouse, where the data transformations are managed with a project, as is most commonly the case with dbt.
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We’re excited to start our new blog series dedicated to conversations with data leaders. Each post will explore their challenges, innovations, and lessons learned in navigating the ever-evolving data landscape. We will be highlighting challenges they have overcome, pain points and the achievements they take the most pride in.
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CRM systems have long served as the primary hub for customer data. Platforms like Salesforce and HubSpot excel at tracking customer interactions, managing sales pipelines, and providing basic reporting. These functions have made CRMs indispensable for sales and marketing teams seeking a centralized view of customer relationships.
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In recent years, the concept of fractional professionals has gained significant traction, especially in tech companies. Fractional executives, such as fractional CFOs, CMOs, and RevOps, provide their expertise to organizations on a part-time or project basis, offering a cost-effective and flexible solution for companies that may not require or cannot afford full-time executives in these roles.
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In modern data pipelines, continuous data integration and data frequent updates may cause unintended data errors. Blue-green Deployment ensures a final checkpoint for accurate results. In this blog, details are provided on how to implement blue green deployment in a data warehouse project.
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