Data Management Data Mining Data Quality Data Warehouse 
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.
Astera
NOVEMBER 27, 2023
Clean and accurate data is the foundation of an organization’s decision-making processes. However, studies reveal that only 3% of the data in an organization meets basic data quality standards, making it necessary to prepare data effectively before analysis. This is where data profiling comes into play.
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Astera
JANUARY 23, 2024
Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.
Astera
MAY 6, 2024
What Is Data Mining? Data mining , also known as Knowledge Discovery in Data (KDD), is a powerful technique that analyzes and unlocks hidden insights from vast amounts of information and datasets. What Are Data Mining Tools? Type of Data Mining Tool Pros Cons Best for Simple Tools (e.g.,
Astera
DECEMBER 21, 2022
A voluminous increase in unstructured data has made data management and data extraction challenging. The data needs to be converted into machine-readable formats for analysis. However, the growing importance of data-driven decisions has changed how managers make strategic choices.
Data Pine
JANUARY 24, 2021
This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?
Astera
FEBRUARY 27, 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.
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