Data Governance Data Integration Data Quality Forecasting 
erwin
APRIL 29, 2020
Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. For example, the marketing department uses demographics and customer behavior to forecast sales.
AWS Big Data
JULY 13, 2023
Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders.
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AWS Big Data
MARCH 26, 2024
A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.
CIO Business Intelligence
FEBRUARY 16, 2023
Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.
Jet Global
MARCH 4, 2024
Data inconsistencies become commonplace, hindering visibility and inhibiting a holistic understanding of business operations. This lack of integration makes it difficult to track progress, measure performance, and identify potential issues. Data governance and compliance become a constant juggling act. Don’t believe us?
FineReport
APRIL 9, 2024
Among the latest BI trends , advanced analytics and predictive modeling stand out as key focal points, enabling businesses to extract deeper insights from their data assets. In addition to these advancements, another prominent trend in data analysis is the growing impact of data visualization.
Jet Global
FEBRUARY 23, 2024
Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. The first step of data mapping is defining the scope of your data mapping project.
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