Dataversity
MARCH 21, 2022
While data lakes and data warehouses are both important Data Management tools, they serve very different purposes. If you’re trying to determine whether you need a data lake, a data warehouse, or possibly even both, you’ll want to understand the functionality of each tool and their differences.
Dataversity
DECEMBER 7, 2020
Data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations who seek to empower more and better data-driven decisions and actions throughout their enterprises. These groups want to expand their user base for data discovery, BI, and analytics so that their business […].
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Astera
FEBRUARY 28, 2024
52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.
ElegantJ BI
MARCH 19, 2021
When considering the advantages of data popularity and sharing, one must also consider that not all popular data will be high-quality data (and vice versa). So, there is definitely a need to provide both approaches in data analysis.
ElegantJ BI
MARCH 19, 2021
When considering the advantages of data popularity and sharing, one must also consider that not all popular data will be high-quality data (and vice versa). So, there is definitely a need to provide both approaches in data analysis. Original Post : Data Agility and ‘Popularity’?
ElegantJ BI
MARCH 19, 2021
When considering the advantages of data popularity and sharing, one must also consider that not all popular data will be high-quality data (and vice versa). So, there is definitely a need to provide both approaches in data analysis. Original Post : Data Agility and ‘Popularity’?
Analysts Corner
AUGUST 13, 2023
Understand Data Structure: Data profiling helps in understanding the structure and format of the data, such as the number of columns, data types, and data format. The Process of Data Profiling The data profiling process typically involves the following steps: 1.
Expert insights. Personalized for you.
246 
Let's personalize your content