IBM Journey to AI blog

SEPTEMBER 2, 2024

Delivering projects on time and within budget often took precedence over long-term data health. Data engineers often missed subtle signs such as frequent, unexplained data spikes, gradual performance degradation or inconsistent data quality. Better data observability unveils the bigger picture.

Data Integration 130

Data Integration Data Quality AI AI 130

Pickl AI

NOVEMBER 4, 2024

Data modelling is crucial for structuring data effectively. It reduces redundancy, improves data integrity, and facilitates easier access to data. Key components of data warehousing include: ETL Processes: ETL stands for Extract, Transform, Load. ETL is vital for ensuring data quality and integrity.

Data Quality 52

Data Quality ETL Data Integration Machine Learning 52

Marktechpost

AUGUST 10, 2024

They must meet strict standards for accuracy, security, and data quality, with ongoing human oversight. With this new legislation, organizations that design and employ AI, particularly those with high-risk systems, must adhere to stringent requirements of openness, data integrity, and human monitoring.

Artificial Intelligence 130

Artificial Intelligence Artificial Intelligence AI AI 130

Pickl AI

MAY 30, 2024

It’s crucial to grasp these concepts, considering the exponential growth of the global Data Science Platform Market, which is expected to reach 26,905.36 billion INR by 2026, with a CAGR of 27.7%. Similarly, the Data and Analytics market is set to grow at a CAGR of 12.85% , reaching 15,313.99 billion INR by 2027.

Data Analysis 52

Data Analysis Data Science Data Scientist Data Quality 52

TransOrg Analytics

OCTOBER 17, 2024

The success of Generative AI heavily depends on the quality of the data it learns from. Poor-quality or incomplete data can lead to inaccurate or biased outputs, making it essential for enterprises to invest in data integration and governance frameworks.

Generative AI 52

Generative AI AI AI Explainability 52