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How AI is Changing the Data Integration Process 

Astera

These algorithms can identify patterns in data and use machine learning (ML) models to learn and adapt to new data sources. The perfect application of this would be in industries such as healthcare, where medical images such as X-rays and MRIs contain important diagnostic information.

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How AI Is Transforming the Future of Business Intelligence and Analytics 

Astera

As AI technology continues to evolve and mature, its integration into business intelligence and analytics unlocks new opportunities for growth and innovation. However , a Forbes study revealed up to 84% of data can be unreliable. Luckily, AI- enabled data prep can improve data quality in several ways.

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Big Data Security: Protecting Your Valuable Assets

Astera

Big Data Security: Protecting Your Valuable Assets In today’s digital age, we generate an unprecedented amount of data every day through our interactions with various technologies. The sheer volume, velocity, and variety of big data make it difficult to manage and extract meaningful insights from. How is big data secured?

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Snowflake ETL Tools: Top 7 Options to Consider in 2024

Astera

Snowflake has restructured the data warehousing scenario with its cloud-based architecture. Businesses can easily scale their data storage and processing capabilities with this innovative approach. Seamlessly automate and orchestrate your data integration workflows, reducing manual intervention and streamlining operations.

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Data Vault vs. Data Mesh: Choosing the Right Data Architecture?

Astera

It ensures that data from different departments, like patient records, lab results, and billing, can be securely collected and accessed when needed. Selecting the right data architecture depends on the specific needs of a business. Use Cases Choosing between a Data Vault and a Data Mesh often depends on specific use cases.

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What is Data Preprocessing? Definition, Importance, and Steps

Astera

Data transformation can also be used to create new attributes within the dataset. Example: A healthcare data analyst leverages mathematical expressions to create new features like Body Mass Index (BMI) through existing features like height and weight. It enables innovative features from existing data, refining model performance.