Accessibility Data Governance Data Pipeline High Quality Data 
Data Engineering Weekly
MARCH 3, 2024
Here is the agenda, 1) Data Application Lifecycle Management - Harish Kumar( Paypal) Hear from the team in PayPal on how they build the data product lifecycle management (DPLM) systems. 3) DataOPS at AstraZeneca The AstraZeneca team talks about data ops best practices internally established and what worked and what didn’t work!!!
Monte Carlo
JANUARY 3, 2024
Let me give you a hint: high-quality proprietary data. It gives the LLM access to that enterprise proprietary data. This is a widely shared sentiment across many data leaders I speak to. If the data team has suddenly surfaced customer-facing, secure data, then they’re on the hook.
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Databand.ai
AUGUST 30, 2023
Benefits of a Data Quality Strategy Implementing a robust data quality strategy offers numerous benefits that directly impact your business’s bottom line and overall success. Additionally, high-quality data reduces costly errors stemming from inaccurate information.
Databand.ai
AUGUST 30, 2023
To maintain data integrity, organizations implement various processes and controls, such as data validation, access controls, backups, and audits. Data validation checks help identify errors and inconsistencies in data, while access controls restrict unauthorized users from accessing or modifying data.
Precisely
MARCH 14, 2023
First, private cloud infrastructure providers like Amazon (AWS), Microsoft (Azure), and Google (GCP) began by offering more cost-effective and elastic resources for fast access to infrastructure. Cloud-native data execution is just the beginning. Simply design data pipelines, point them to the cloud environment, and execute.
Databand.ai
JULY 5, 2023
What Are Data Observability Tools? Data observability tools are software solutions that oversee, analyze, and improve the performance of data pipelines. Data observability tools allow teams to detect issues such as missing values, duplicate records, or inconsistent formats early on before they affect downstream processes.
Monte Carlo
JUNE 16, 2023
Data quality has broad applications across industries, but its importance and degree of quality required is also contextual to the use case. For example, in marketing, high-quality data can help businesses better understand their customers, allowing them to create more targeted and effective campaigns.
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