Data + AI Blog

Learn more about Smarter risk and compliance on our new hub. The core function of a bank is to protect assets, identify risks and mitigate losses by protecting customers from fraud, money laundering and other financial crimes. In today’s interconnected and digital world, managing risk and regulatory compliance is an increasingly complex and costly endeavor....

The decision to migrate from Hadoop to a modern cloud-based architecture like the lakehouse architecture is a business decision, not a technology decision. In a previous blog, we dug into the reasons why every organization must re-evaluate its relationship with Hadoop. Once stakeholders from technology, data, and the business make the decision to move the...

Apache Hadoop was created more than 15 years ago as an open source, distributed storage and compute platform designed for large data sets and large-scale batch processing. Early on, it was cheaper than traditional data storage solutions. At the time, businesses didn't need to run it on particular hardware. The Hadoop ecosystem also consists of...

Leveraging data (internal and external) and customer analytics to innovate and create competitive advantages is more powerful than it has ever been. This popular practice is fueled by the growing volume of operational and customer data and technological advancements that make extracting value from data even faster and more accessible. Driving more value from all...

The Chief Data Officer (CDO) is not a new position – Capital One reportedly had a CDO all the way back in 2002. But only recently has it become a mainstream, business-critical role for enterprises. In a recent study by NewVantage Partners, 65% of surveyed companies have a CDO position within their organization. And as...

ビッグデータを扱う人が最初に直面したデータの課題は、整合性でした。データの量が少なく、ソースのバリエーションも限られていた頃は、構造化データのテーブルで構成されたリレーショナルデータベース（RDB・関係データベース）の使用で事足りていましたが、アプリケーションが普及するようになると、複数のアプリケーションに同じデータが異なる値で現れ、データの整合性がとれないという課題が発生しました。どのデータが正しいかを判断するには、数あるアプリケーションの中から、どのバージョンのデータを使うべきかを見極めなくてはなりません。もしユーザーが適切なバージョンのデータを使用できなければ、判断を誤ってしまう可能性もあります。

The Industrial Internet of Things (IIoT) is already driving massive productivity gains in the Manufacturing and Energy & Utilities industries through decreased waste, automated quality control, predictive maintenance (increasing overall equipment effectiveness) and optimized energy consumption...just to name a few. At the same time, internet-enabled equipment and IoT devices present a cybersecurity vulnerability, particularly to...

Only 13% of organizations -- super achievers -- are succeeding at their data and AI strategy yet the successful application of data and AI has never been a greater necessity for survival than now1. In order to remain forward-thinking in today’s landscape, data leaders are looking for the ability to eliminate silos that traditionally separate...

With the fast-moving evolution of the data lake, Billy Bosworth and Ali Ghodsi share their mutual thoughts on the top 5 common questions they get asked about data warehouses, data lakes and lakehouses. Coming from different backgrounds, they each provide unique and valuable insights into this market. Ali has spent more than 10 years on...

After six episodes featuring amazing leaders and practitioners in the data and AI community, we wrapped up season 1 of Data Brew by Databricks, our homegrown podcast hosted by us two - Denny and Brooke. This season focused on all things lakehouses - combining the key features of data warehouses, such as ACID transactions, with...