Teams have more peace
Posted: Sun May 25, 2025 5:51 am
of mind knowing that data is reliable and relevant, and that clear standards and practices exist to protect data to reduce the likelihood of a breach.
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Data harmonization
Data harmonization is the process of bringing together data from multiple sources to create a unified dataset that functions as if it were a single data source. It involves aligning data elements, formats, and structures to eliminate inconsistencies and make the data easier to compare and analyze.
What it means for customers: Customers get a consistent experience across departments because organizations can access data, like customer preferences and purchase history, from various sources as if it were a single source.
What it means for teams: Teams have a more holistic afghanistan phone number list view of customers and can access and analyze information more quickly, without having to access multiple systems.
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Data insights and real-time insights
Data insights are key findings, like data patterns and trends, that you get from data analysis. Real-time insights are the immediate and up-to-date information from data analysis that comes in the moment an event occurs, such as sales through an ecommerce site. You can use these insights to guide decision-making and strategies.
What it means for customers: Data insights lead to key customer benefits across all brand interactions, including more tailored products and services, and proactive support. With real-time insights, organizations can create real-time personalization, more targeted marketing, and nearly immediate responses to issues.
What it means for teams: Teams build a competitive advantage in the market, using data insights to gain a deeper understanding of customers, improve processes, and fuel smart decisions.
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Data lake
A data lake is a centralized storage repository of raw data. It’s a vast, flexible, and low-cost storage system organizations use to collect and store large volumes of structured, unstructured, and semi-structured data in its original format. Data lakes capture a wealth of unstructured data like social media posts, sensor logs, and location data.
(Back to top)
Data harmonization
Data harmonization is the process of bringing together data from multiple sources to create a unified dataset that functions as if it were a single data source. It involves aligning data elements, formats, and structures to eliminate inconsistencies and make the data easier to compare and analyze.
What it means for customers: Customers get a consistent experience across departments because organizations can access data, like customer preferences and purchase history, from various sources as if it were a single source.
What it means for teams: Teams have a more holistic afghanistan phone number list view of customers and can access and analyze information more quickly, without having to access multiple systems.
(Back to top)
Data insights and real-time insights
Data insights are key findings, like data patterns and trends, that you get from data analysis. Real-time insights are the immediate and up-to-date information from data analysis that comes in the moment an event occurs, such as sales through an ecommerce site. You can use these insights to guide decision-making and strategies.
What it means for customers: Data insights lead to key customer benefits across all brand interactions, including more tailored products and services, and proactive support. With real-time insights, organizations can create real-time personalization, more targeted marketing, and nearly immediate responses to issues.
What it means for teams: Teams build a competitive advantage in the market, using data insights to gain a deeper understanding of customers, improve processes, and fuel smart decisions.
(Back to top)
Data lake
A data lake is a centralized storage repository of raw data. It’s a vast, flexible, and low-cost storage system organizations use to collect and store large volumes of structured, unstructured, and semi-structured data in its original format. Data lakes capture a wealth of unstructured data like social media posts, sensor logs, and location data.