Life Sciences

Hyeshin Hwang 0
더 나은 세상을 만드는 방법

공공 고객 세미나 통해 공중보건과 공공사회서비스 개선을 위한 해법 제시 SAS코리아는 지난 5월 23일과 24일 양일간 공공 부문 고객들을 대상으로 ‘공중보건 전문가를 위한 SAS Public Health 세미나’와 ‘공공사회서비스 전문가를 위한 SAS Social Services 세미나’를 JW메리어트 호텔에서 개최했습니다. [사진1] 공중보건 전문가를 위한 SAS Public Health 세미나 장면 소외 계층 없이 전

Advanced Analytics | Analytics | Artificial Intelligence | Data Management | Data Visualization
Amaya Cerezo 0
Construyendo el ‘Máster Data Scientist’: el jedi de los datos al servicio de la estrategia

En los últimos años, la ciencia de datos ha experimentado un crecimiento exponencial y se ha convertido en un pilar fundamental para las estrategias de las organizaciones en todas las industrias. Sin embargo, para los data scientist experimentados, el panorama del dato se encuentra  en un proceso de cambio constante.

Artificial Intelligence | Innovation
Greg Wujek 0
How generative AI creates cross-channel harmony in pharmaceutical marketing

The days of one-size-fits-all messaging in the pharmaceutical industry are fading. Today's patients and health care providers (HCPs) expect personalized content across a variety of channels. This is where generative AI (GenAI) can really help execute cross-channel marketing. Reaching the right audience with the right message Imagine a world where

Advanced Analytics | Analytics | Artificial Intelligence | Data for Good
Ronaldo Costa 0
Modelos preditivos em saúde: apoio à gestão e ao bem-estar dos pacientes

Cada vez mais as ferramentas de IA apoiam a tomada de decisão e ajudam na criação modelos que identificam tendências e padrões de comportamentos que, juntamente com regras de negócios, permitem que as empresas tomem decisões mais assertivas, seja qual for sua área de atuação. As análises mais avançadas incluem

Analytics | Artificial Intelligence | Customer Intelligence
Sofia Real 0
A transformação MarTech: como a tecnologia irá melhorar o marketing em 2024

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

データ分析効率化の秘訣:SAS ViyaとAzure Synapseの高速データ転送方法の紹介

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

Data Management | Innovation | Predictions
Vrushali Sawant 0
3 industries set to benefit from ethical synthetic data generation in 2024

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

Jeff Alford 0
How accurate were our 2023 predictions in health care, technology and more?

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

Analytics | Learn SAS
Catherine (Cat) Truxillo 0
5 claves para crear equipos de analítica más sólidos

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

Soundarya Palanisamy 0
3 ways ESG will impact the health care and life sciences industry

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

Advanced Analytics | Analytics | Cloud | Data Management
Kayt Leonard 0
5 tips for choosing a statistical computing environment

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

Advanced Analytics | Artificial Intelligence | Data Visualization | Machine Learning
Jessica Curtis 0
How to cultivate trust in analytical models and improve forecast adoption

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

Analytics | Machine Learning
Charlie Chase 0
How life science and health care supply chains can adapt to disruption

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

Pippa White 0
Life sciences: now is the time to embrace analytics in the cloud

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

Analytics | Learn SAS | Students & Educators
Gaetano Varriale 0
Collaboration is key to developing data specialists in Italy

"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

Advanced Analytics | Analytics
Soundarya Palanisamy 0
Decentralizing clinical trials: how COVID-19 has changed drug development

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.

Analytics | Artificial Intelligence
Mark Lambrecht 0
Vijf uitdagingen in de zorg waar analytics en AI in 2022 bij kunnen helpen

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

Analytics | Data for Good | Students & Educators
Alyssa Farrell 0
Addressing health inequities and closing the cancer care gap with data and technology

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

Analytics | Data Visualization
Joon-Hyung Koh 0
AI 기반의 쉽고 간단한 Clinical Data 탐색 및 시각화 #2편

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

Analytics | Artificial Intelligence | Data Visualization
Joon-Hyung Koh 0
AI 기반의 쉽고 간단한 Clinical Data 탐색 및 시각화 #1편

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

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