LIXIL:BigQuery を中心としたデータ活用基盤 LIXIL Data Platform を構築、"データ活用の民主化" を推進 これまでも Google Cloud を有効活用してきた株式会社LIXIL(以下、LIXIL)。これからの新時代に向け、さまざまな先進的な取り組みを行っている同社ですが、中でも注目すべき取り組みが、BigQuery を中心としたデータ活用基盤『LIXIL Data Platform(以下、LDP)』です。"データ活用の民主化" を掲げ、2021 年 5 月に正式運用開始されたこの仕組みが、今、どのように LIXIL を変えようとしているのかを聞いてきました。 利用している Google Cloud ソリューション:スマート アナリティクス 利用している Google Cloud サービス:BigQuery、BigQuery ML、Data Catalog
In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data. The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. The principles emphasise machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with non
Large-scale companies serve millions or even billions of people who depend on the services these companies provide for their everyday needs. To keep these services running and delivering meaningful experiences, the teams behind them need to find the most relevant and accurate information quickly so that they can make informed decisions and take action. Finding the right information can be hard for
Imagine you are a business leader ready to start your day, but you wake up to find that your daily business report is empty — the data is late, so now you are blind. Over the last year, multiple teams came together to build SLA Tracker, a visual analytics tool to facilitate a culture of data timeliness at Airbnb. This data product enabled us to address and systematize the following challenges of d
Image courtesy of Andrey_Kuzmin on ShutterstockAs companies increasingly leverage data to power digital products, drive decision making, and fuel innovation, understanding the health and reliability of these most critical assets is fundamental. For decades, organizations have relied on data catalogs to power data governance. But is that enough? Debashis Saha, VP of Engineering at AppZen, formerly
Do you know what kind of sensitive data your organization holds? Are you keeping track of every change applied across all your tables and columns? Are you confident to answer questions an auditor may have on data regulations? Having an auditor knocking in your door is not the scariest thing, data breaches can be way scarier! From fines to customer loss and legal ramifications — the consequences ca
High level data process The data discovery issues at Shopify can be categorized into three main challenges: curation, governance, and accessibility. Curation “Is there an existing data asset I can utilize to solve my problem?” Before Artifact, finding the answer to this question at Shopify often involved asking team members in person, reaching out on Slack, digging through GitHub code, sifting thr
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