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Data Learning Center

Comprehensive resources on data engineering and data infrastructure

Customer Data

What Is Customer Data?

This article gives a definition of customer data, as well as explaining the different types of customer data, how customer data is collected, why it is important, and whether collecting customer data is legal.

Customer Data Analytics

Customer data analytics is generating inferences from data that’s coming directly from your customers, or is inferred through their actions in your SaaS product, website, and campaigns. This article helps you choose the right processes for the job.

Customer Data Management

Customer data management (sometimes known as “customer database management”) is a common umbrella term for the strategies a company uses to collect, control and use its customer data.

Collecting Customer Data

It’s no secret that data has become the most precious commodity to today’s leading businesses. When properly mined, data can enable powerfully effective marketing and game-changing growth strategies.

CDPs vs. DMPs

Customer data management has recently undergone changes with the tools used to handle customer data. This article will help illustrate the difference between two of these tools — customer data platforms (CDPs) and data management platforms (DMPs).

Types of Customer Data

Customer data is both a valuable business asset that can be used for marketing and business growth, as well as a sensitive source of information about individuals that must be protected.

Customer Data Protection

Customer data protection is vital for avoiding PII data breaches and their legal and reputational consequences. In this article, find out how to protect your customer data.

What is Identity Resolution?

Identity resolution is the process of combining personal information gathered by a website to generate a complete view of customers for enhanced data analysis.

What Is a Customer Data Platform?

This article defines a customer data platform (CDP), and explains the different types of CDPs. It also weighs the pros and cons of buying software vs building your own.

What is an Identity Graph?

Identity graphs are used to filter redundant customer data and connect potentially billions of points in a complex, scalable web of people and behavior.

Data Warehouse

How to Create and Use Business Intelligence with a Data Warehouse

In this article, we cover what business intelligence (BI) is, which roles within the company work with it, and explain BI's relationship to the data warehouse.

Data Warehouse Architecture

Data warehouses need to be architected in a way that maximizes flexibility and maintains speed. In this article, you'll learn about data warehouse architectures, as well as what you should consider when setting up your own data warehouse.

Best Practices for Accessing Your Data Warehouse

In this article, you will learn how data is stored in a data warehouse, how it’s accessed, best practices for writing SQL queries, who the major cloud data warehouse vendors are, and the various types of data storage models available.

What Is a Data Warehouse?

Data warehouses offer a wide range of benefits. In this article, you’ll learn about the benefits and features of a data warehouse and how to effectively implement, use, and maintain a data warehouse.

Data Warehouse Best Practices — preparing your data for peak performance

One of the best modern tools for maximizing the observability and analytic power of your data is the data warehouse. This article will guide you through data warehouse best practices and illustrate how to get the most value from your data warehouse.

How do Data Warehouses Enhance Data Mining?

Everyone’s saying it more and more, and in increasingly tired metaphors: data is a new currency. This article covers key ways in which data warehouses enhance the data mining process.

Data Warehouses versus Databases: What’s the Difference?

Understanding the sometimes-subtle differences between types of data infrastructure can be challenging. This article will explain the differences and the best usages of a data warehouse as opposed to a database.

What are the Benefits of a Data Warehouse?

A data warehouse is a software construct that pulls data from different sources into a single target for business intelligence analysis and support for strategic decisions. In this article, we examine the benefits of implementing a data warehouse.

Key Concepts of a Data Warehouse

This article covers key concepts of the data warehouse, comparing its capabilities with that of relational databases, data marts, and data lakes — all common solutions to the challenges of consuming large, varied types of data.

Data Warehouses versus Data Lakes

Data warehouses and data lakes occupy different positions in the tradeoff between responsiveness, resource costs, and flexibility. In this article, we explore their differences.

Data Warehouses versus Data Marts

In the worlds of business intelligence and outcome modeling, the terms data warehouse and data mart are often used interchangeably. The differences are worth knowing, though, so in this article we’ll compare and contrast the two.

How to Move Data in Data Warehouses

In this article, we’ll explore the various ways that data enters, moves through, and exits warehouses. You’ll also learn how a data warehouse strategy helps businesses understand their current position and set benchmarks to drive long-term growth.

Difference Between Big Data and Data Warehouses

Although terms “big data” and “data warehouse” are often compared directly, there is a categorical difference between them. We will cover the difference in this article.

Data Security

What is Consent Management?

This article explains how consent management enables you to establish trust with your users and ensure your data operations are within regulatory compliance.

What is Persistent Data?

”Persistent” data is stored on media from which it is accessible for the long term. This article explains persistent data terminology and best practices.

Data Access Control

This article explains data access controls and why your organization must implement them to safeguard your valuable data and protect you from liability.

Data Sharing and Third Parties

Third-party data is important for building market insights and requires careful handling. This article explains third-party data terminology and best practices.

What is PII Masking and How Can You Use It?

PII masking protects sensitive user information by changing data across a database. This article discusses techniques and concepts in PII masking.

Data Security Strategies

A data protection strategy can avoid costly data breaches and protect your reputation and business assets. Learn the key components of a data security strategy.

How To Handle Your Company’s Sensitive Data

Damages from sensitive data loss can be devastating for companies. It can destroy customer trust and lead to financial and legal consequences. In this article, you will learn about sensitive data within a company and how best to protect it.

How to Manage Data Retention

In this article, you’ll learn more about what data retention is and why a data retention policy is valuable to your organization. You’ll also learn some of the core ideas behind data retention policies and some best practices for creating your own.

Data Security Best Practices For Companies

In this article, you’ll learn about best practices in data security as well as concepts that you should know about in order to protect a company’s digital infrastructure.

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