Life Sciences

Artificial Intelligence
David Shannon 0
Trust in the process: Hyperautomation for drug development accelerates time-to-market

AI and automation – often referred to as hyperautomation – are evolving rapidly with industry experts emphasizing their increasing ability to operate independently and make intelligent decisions. By combining powerful generative AI with business expertise, organizations can accelerate and streamline their processes like never before. I recently sat down with Mayank

Advanced Analytics | Analytics | Cloud | Data Management
Kayt Leonard 0
5 tips voor het kiezen van een statistische rekenomgeving

Wanneer je denkt aan levensreddende technologie, denk je dan aan een statistische computeromgeving? Statistische rekenomgevingen (SCE) zijn essentieel voor het bevorderen van wetenschappelijke ontdekkingen door onderzoekers de mogelijkheid te bieden om gegevens efficiënt en volgens de regels te beheren, verwerken en analyseren, waarbij de integriteit van de regelgeving zo goed

Advanced Analytics | Analytics | Cloud | Data Management
Kayt Leonard 0
5 consejos para elegir un entorno informático estadístico

Cuando piensa en tecnología que salva vidas, ¿le viene a la mente un entorno informático estadístico? Los entornos de cálculo estadístico (SCE, por sus siglas en inglés) son fundamentales para acelerar los descubrimientos científicos, ya que permiten a los investigadores gestionar, procesar y analizar los datos de forma eficiente y

Advanced Analytics | Analytics | Cloud | Data Management
Kayt Leonard 0
5 consigli per scegliere un ambiente di calcolo statistico

Ti viene in mente un ambiente di calcolo statistico, quando pensi alle tecnologie salvavita? Eppure gli ambienti di calcolo statistico (Statistical computing environment, SCE) sono determinanti per accelerare le scoperte scientifiche, in quanto consentono ai ricercatori di gestire, elaborare e analizzare i dati in modo efficiente e rigoroso, mantenendo la

Advanced Analytics | Analytics | Cloud | Data Management
Kayt Leonard 0
5 Tipps zur Auswahl einer statistischen Rechenumgebung

Denken Sie bei lebensrettender Technologie an eine statistische Rechenumgebung? Umgebungen für statistische Berechnungen (SCE) sind für die Beschleunigung wissenschaftlicher Aufdeckungen von entscheidender Bedeutung. Sie ermöglichen es Forschern, Daten effizient und konform zu verwalten, zu verarbeiten und zu analysieren, unter Wahrung der größtmöglichen regulatorischen Integrität. Da die Forschung im Bereich der

Advanced Analytics | Analytics | Cloud | Data Management
Kayt Leonard 0
5 tips til at vælge et statistisk databehandlingsmiljø

Når du tænker på livsvigtig teknologi, kommer du så til at tænke på et statistisk databehandlingsmiljø? Statistiske databehandlingsmiljøer (SCE) er afgørende for at fremskynde videnskabelige opdagelser ved at gøre det muligt for forskere at administrere, behandle og analysere data effektivt og i overensstemmelse med reglerne og opretholde den største lovgivningsmæssige

Advanced Analytics | Analytics | Data Management | Data Visualization
Javier López Gómez 0
La importancia de tener buenos datos de entrada en los modelos analíticos

En la actualidad, los modelos analíticos son herramientas esenciales para tomar decisiones basadas en datos. Desde prever tendencias hasta optimizar operaciones, los modelos analíticos dependen en gran medida de la calidad de los datos de entrada. La precisión, integridad y relevancia de estos datos son cruciales para obtener resultados confiables

Artificial Intelligence | Predictions
Lisa Murch 0
Transforming cancer care with radiomics: The future depends on data sharing

A woman arrives at the emergency room with chest pain. She immediately receives an x-ray. While the radiologist looks at the image, her AI assistant flags anomalies in the patient’s lungs – invisible without the technology. The chest pain turns out to be benign, but sophisticated imaging reveals early-stage lung

Analytics
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

Analytics
0
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

Predictions
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

Analytics
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