No ano passado, assistimos a uma revolução notável no desenvolvimento de modelos generativos de IA e na sua adoção generalizada por indivíduos e empresas. Dois exemplos claros foram o ChatGPT e o DALL-E da OpenAI que, em apenas alguns meses, conseguiram conquistar milhões de utilizadores em todo o mundo, garantindo
Life Sciences
1.背景 データ管理と分析の世界では、効率的かつ迅速なデータの転送と書き込みは極めて重要です。特に大規模なデータウェアハウスサービスを利用する際には、このプロセスの最適化が不可欠です。Azure Synapse Analyticsは、そのようなサービスの一つとして注目を集めており、SAS Viyaを使用する多くの企業やデータアナリストも、より効率的なデータハンドリングを追求しています。 SAS ViyaのユーザーはSAS/ACCESS to Microsoft SQL Serverを使用してAzure Synapseにデータを転送および書き込む際に、より高いデータ書き込み効率と転送速度を求めるのは当然です。データ処理能力をさらに強化し、書き込み効率を高めるために、SAS Access to SynapseのBulkLoad機能は非常に優れた選択肢です。BulkLoad機能はデータの書き込み速度を大幅に向上させるだけでなく、Azure Data Lake Storage Gen 2(以下、ADLS2と称する)を利用して、安定かつ安全なデータストレージおよび転送環境を提供します。 ただし、BulkLoad機能を使用する際にはADLS2の設定と構成が関わってくるため、構成および使用のプロセスが複雑に感じられたり、疑問が生じたりすることがあります。このブログの目的は、管理者およびユーザーに対して、明確なステップバイステップの設定プロセスを提供し、構成の過程で見落とされがちなキーポイントを強調することで、設定時の参考になるようにすることです。 以下は本記事内容の一覧です。読者は以下のリンクをで興味のあるセクションに直接ジャンプすることができます。 2.Bulkload機能について 3.BULKLOAD機能を利用するためのAzure側で必要なサービスの作成 3-1.Azure Data Lake Storage (ADLS) Gen2のストレージアカウントの作成 3-2.ストレージアカウントのデータストレージコンテナの作成 3-3.ストレージアカウントの利用ユーザー権限の設定 3-4.データ書き込み用のSASコードの実行 3-5.Azureアプリの設定 4.SAS Viya側の設定とAzure Synapseへの接続 4-1.SAS Studioでの設定 4-2.Azure SynapseのSQLデータベースをSASライブラリとして定義 4-3.Azure Synapseへデータの書き込み 2.Bulkload機能について なぜSAS ViyaがBulkload機能を使用してAzure Synapseに効率的にデータを書き込む際にADLS2サービスが必要なのか、そしてそのプロセスがどのように行われるのかを説明します。 Azure Synapse Analyticsは、柔軟性が高く、高いスループットのデータ転送を可能にするために、COPY
The health care and life sciences market is accelerating – but not without a few necessary pitstops. Machine learning, digital twins, generative AI, robots as doctors, medications with sensors, and surgery at the speed of light. It’s all driving the market. Year after year, market researchers, analyst firms, and industry
In 2024, we will witness the proliferation of synthetic data across industries. In 2023, companies experimented with foundational models, and this trend will continue. Organizations see it as an emerging force to reshape industries and change lives. However, the ethical implications can't be overlooked. Let’s explore some industries I think
As 2023 ends, it's important to reflect on the predictions that SAS leaders made at the beginning of the year. Let’s look at some of these predictions and see how accurate they were. We'll explore forecasts related to health care, human resources, AI, data, renewable energy and more. Let's dive
Debido a la complejidad y cambios en el mercado, las organizaciones de todo el mundo están aprovechando las oportunidades para hacer mejores predicciones, identificar soluciones y dar pasos estratégicos y proactivos, lo que significa que dependen cada vez más de los big data. Sin embargo, en su búsqueda de resistencia
Health care and life science organizations have always prioritized saving lives and now extend that commitment to environmental, social and governance (ESG) goals. They are not merely checking boxes, but genuinely pursuing long term impact for individuals, future generations and the planet. However, they must now elevate their ESG efforts to
When you think about life-saving technology, does a statistical computing environment come to mind? Statistical computing environments (SCE) are critical in accelerating scientific discoveries by enabling researchers to manage, process and analyze data efficiently and compliantly, maintaining the utmost regulatory integrity. As life sciences research generates increasingly large and diverse
As in most other sectors, health care is changing at lightning speed. Access to data makes it possible to speed up clinical trials, develop more personalized medication, make quicker and better diagnoses, improve the quality of patient care and save lives. The pandemic has sped up digital transformation in every
Getting a new medicine to market is a marathon, not a sprint. Or perhaps a better analogy is a steeplechase, where competitors must overcome gruelling obstacles on their way to the finish line. Clinical trials are one of the biggest hurdles on the route to market and they’re getting more
Even with today's technology, it's hard to know precisely when, where and how weather-related damage will occur. Flooding costs are expected to rise drastically during the next 20 years and climate change is a constant threat. Unfortunately, natural disasters are here to stay, but we can try our best to
Often the biggest challenge when implementing a successful forecasting process has nothing to do with the analytics. Forecast adoption – incorporating forecasts into decision-making – is just as high a hurdle to overcome as the models themselves. Forecasting is more than analytical models Developing a forecasting process typically begins with
Robert Handfield, PhD, is a distinguished professor of Supply Chain Management at North Carolina State University and Director of the Supply Chain Resource Cooperative. In an episode of the Health Pulse Podcast, Handfield gave his views regarding the challenges health care and life science companies have encountered over the past two years
For life sciences companies, effective commercial execution depends on delivering useful information to healthcare providers. How can your business manage engagement intelligently across all channels? The pace of pharmaceutical development is accelerating faster than ever before. During the pandemic, life sciences leaders proved that the industry can react to emerging
Research, supply chain, manufacturing, and sales increasingly depend on partnerships in a digital ecosystem. Cloud-based analytics makes it possible to collaborate intelligently at scale. For years, life sciences companies have been justifiably cautious about moving their data science functions into the cloud. Although the industry’s central purpose is to accelerate
"Companies across pharma and medtech need talented people to cover the range of data-related challenges." Paolo Morelli, Executive VP, Biometrics of Alira Health Paolo Morelli, Executive Vice President, Biometrics of Alira Health, tells us how he developed a relationship between the University of Bologna and industry-leading companies – and what
The COVID-19 pandemic brought an enormous urgency to the life sciences sector. Companies vied for suitable treatments and in less than a year, COVID-19 vaccines were developed. This demonstrated clearly that the sector could move at speed when necessary. Though vaccines were supported by regulators, inefficiencies in vaccine and drug development were exposed.
Rainforests are a vital part of the climate and life on our planet. Rainforests are known as ‘the lungs of the Earth’ because they produce 20% of the world’s oxygen. Because of this, conservation efforts are more important than ever. By combining the power of AI and analytics technologies with
Geen sector die de afgelopen twee jaar zo hard onder druk stond als de gezondheidszorg. En ook nu het einde van de pandemie in zicht lijkt, zullen veel uitdagingen rond Healthcare en Life Sciences niet verdwijnen. Gelukkig investeren zowel overheden als ziekenhuizen en farmaceutische bedrijven fors in data en analytics
Inequities in cancer care cause specific populations in the U.S. and worldwide to bear a more significant burden of disease than the general population, based upon barriers. These barriers to prevention and care have long existed but were undeniably exacerbated by the COVID-19 pandemic. February 4 marks World Cancer Day, which
Amid historical and structural barriers, “quality cancer treatment for all” is a simple credo that is not easy to put into action. Cancer is recognized as a leading cause of death, accounting for more than 10 million deaths globally in 2020, according to the World Health Organization. Globally, people with
지난 블로그 포스팅 #1편에서는 임상시험 전 과정에 참여한 내.외부 모든 이해관계자가 임상시험 데이터에 쉽게 접근하여 진행 상황을 파악할 수 있도록 지원하는 SAS Visual Analytics 솔루션의 기능을 소개해 드렸습니다. 이번 포스팅에서는 이러한 AI기반의 SAS Visual Analytics 분석 솔루션을 활용하여 임상시험 SDTM 데이터의 탐색 및 시각화 리포트의 활용에 대해 알아보겠습니다. Clinical Data
임상시험을 비롯한 모든 업무에서 분석은 필수이며, 점점 고급분석을 필요로하고 있습니다. 이번 블로그 포스팅은 2편으로 나누어 1편에서는 임상시험 전 과정에 참여한 내.외부 모든 이해관계자가 임상시험 데이터에 쉽게 접근하여 진행 상황을 파악할 수 있도록 지원하는 SAS Visual Analytics 솔루션의 기능을 소개합니다. 이어 2편에서는 임상시험의 SDTM 데이터를 활용하여 SAS Visual Analytics 솔루션에 어떻게
Melhorar a vida das pessoas com base em dados, é um dos nossos principais objetivos no SAS. É neste sentido, que uma das categorias dos Curiosity Data Science Iberian Awards, que organizámos este ano pela primeira vez em conjunto com a SPAIN IA e a Data Science Portuguese Association (DSPA),
How long do dogs live? ... That's a good/tough question. Some live longer than others, but what are the determining factors? Let's throw some data to this problem, and see if we can fetch some answers! But before we get started, how about a random picture to get you into
We’ve all experienced the value that innovation has brought to our lives. The cloud, enormous data sets and more accurate AI modeling have enabled many organizations to bring new products and services to market in ways we could not have imagined 20 years ago. The health care and life sciences
Collaboration in the cloud is definitely the next big thing from my perspective for life sciences organisations.
FDA, 의약품 평가 및 연구 센터 위해 SAS 고급분석 및 AI 기술 도입 미국 식품의약국(FDA)은 SAS® Viya® 플랫폼 내 자연어 처리, 인공지능 및 머신러닝 기능 등을 기반으로 새로운 도약을 위해 SAS와 40년 파트너십을 연장하기로 했습니다. 향후 5 년간 4,990 만 달러(약 560억원)에 달하는 총괄 구매 계약(BPA)을 통해 SAS는 FDA에서 진행중인
Safety, efficacy, speed and costs must all be prioritized and balanced in the delivery of life-changing therapies to patients. A drug that's quickly and cost-efficiently delivered to market, but isn’t effective and safe is unacceptable. An effective, safe drug that doesn’t get to patients in time to save lives has
"I was very impressed by how epidemiologists, analytical experts, architects, programmers and others were working together."