Tag: big data quality

How BlaBlaCar Built a Practical Data Mesh to Support Self-Service Analytics at Scale

BlaBlaCar is the largest transportation marketplace in Europe and Latin America for ride-sharing. The company started as a core app that connected drivers and passengers for carpooling, but today, they support multiple modes of transportation-and immense volumes of complex, peer-to-peer, geographic data. /certifications/ The data organization at BlaBlaCar makes sure data flows accurately to consumers, … Continue reading How BlaBlaCar Built a Practical Data Mesh to Support Self-Service Analytics at Scale →

How to Build Data Products Your Company Will Actually Use

Across both public and private sectors, more organizations are adopting a “data-driven” mindset-or, at least, data-driven messaging. But in reality, most aren’t prepared for the reality of what it takes to truly make decisions based on data. /sas-certification/ Teams have to be aligned about what data is used and how decisions are made. Data has … Continue reading How to Build Data Products Your Company Will Actually Use →

Data Quality Management: 6 Stages For Scaling Data Reliability

I like to think of data quality management within the context of physical fitness. You can get in shape with hard work, but staying in shape requires good habits. And above all else it’s a mindset and a lifestyle. You also have to sweat. At least a little bit. No technology, including data observability, can … Continue reading Data Quality Management: 6 Stages For Scaling Data Reliability →

Data Integrity: the Last Mile Problem of Data Observability

Data quality issues have been a long-standing challenge for data-driven organizations. Even with significant investments, the trustworthiness of data in most organizations is questionable at best. Gartner reports that companies lose an average of $14 million per year due to poor data quality. /qsda2021-qlik-sense-data-architect-qsda/ Data Observability has been all the rage in data management circles … Continue reading Data Integrity: the Last Mile Problem of Data Observability →

How Reliable is Big Data in a Constantly Changing, Unpredictable World?

Data’s Backward-Looking Lens – Usefulness Versus Reliance In 2011, ailing US retailer JCPenney recruited Ron Johnson as CEO, the former president of Apple’s retail operations, who is credited with pioneering the concept of the Apple Store. Johnson arrived at JCPenney intent on reinventing the brand and boosting sales. He implemented a broad refurbishment program, creating … Continue reading How Reliable is Big Data in a Constantly Changing, Unpredictable World? →

Assuring Data Quality: How to Build a Serverless Data Quality Gate on AWS

Data is a vital element in business decision-making. Modern technologies and algorithms allow for processing and storage of huge amounts of data, converting it into useful predictions and insights. But they also require high-quality data to ensure prediction accuracy and insight value. In today’s world, the importance of data quality validation is hard to overestimate. … Continue reading Assuring Data Quality: How to Build a Serverless Data Quality Gate on AWS →

5 Strategies For Stopping Bad Data In It’s Tracks

For data teams, bad data, broken data pipelines, stale dashboards, and 5 a.m. fire drills are par for the course, particularly as data workflows ingest more and more data from disparate sources. Drawing inspiration from software development, we call this phenomenon data downtime– but how can data teams proactively prevent bad data from striking in … Continue reading 5 Strategies For Stopping Bad Data In It’s Tracks →