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Data Warehouse or Data Lakes
According to a Gartner study, organizations believe that poor data quality is responsible
for $15 million a year on average in losses. Defining the ideal way to store your data is the first step to help you become more efficient and effective for your business goals.
That’s where Data Warehouses and Lakehouses come in. The difference between a Data Warehouse and a Lakehouse? In short, they’re both important but also different in many ways. Businesses need access to insights from their data in order to make informed decisions about their products, customers and employees. By using one of these data platforms, companies can gain access to more types of information—including structured, or semi-structured and unstructured content—than ever before.
This paper covers:
- The key differences between a Data Lakehouse and Data Warehouse
- Why and how they are important
- What to consider when deciding which platform best suits your needs
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