Systems | Development | Analytics | API | Testing

Picking the right business intelligence (BI) tool is essential to helping you beat your competitors, better serve your customers, and make smarter data-driven decisions. However, there's no one-size-fits-all tool for every enterprise. Not all BI users are created equal, and not all users should have the same level of access to sensitive and confidential data.

Written in Python, Apache Airflow is an open-source workflow manager used to develop, schedule, and monitor workflows. Created by Airbnb, Apache Airflow is now being widely adopted by many large companies, including Google and Slack. Being a workflow management framework, Apache Airflow differs from other frameworks in that it does not require exact parent-child relationships. Instead, you only need to define parents between data flows, automatically organizing them into a DAG (directed acyclic graph).

In the second of this two-part episode of Data+AI Battlescars, Sandeep Uttamchandani, Unravel Data’s CDO, speaks with Kapil Surlaker, VP of Engineering and Head of Data at LinkedIn. In part one, they covered LinkedIn’s challenges related to metadata management and data access APIs. This second part dives deep into data quality.

Personally identifiable information (PII) is some of the most valuable data that organizations can have. It's also some of the most dangerous if you don't follow data security best practices. If you don't treat this data with care, you could end up in the headlines as the victim of the latest data breach, costing you money and damaging your reputation. Of course, you should never leave PII data unprotected. So what is the best way to protect the confidential and sensitive PII that you handle?

Data cleansing is a fundamental aspect of knowing what data you retain and using it most effectively. The process of cleansing reduces the potential for error and enhances data reliability. Here's how to get started.

In the first of this two-part episode of Data+AI Battlescars, Sandeep Uttamchandani, Unravel Data’s CDO, speaks with Kapil Surlaker, VP of Engineering and Head of Data at LinkedIn. In this first part, they cover LinkedIn’s challenges related to Metadata Management and Data Access APIs. Part 2 will dive deep into data quality.

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