Verschieben Sie Ihre Daten genau dahin, wo Sie sie haben möchten: Aus Hadoop heraus, nach Hadoop hinein. Danach können diese Daten für Reports, Visualisierungen und erweiterte Analysen verwendet werden. Klingt einfach? Ist es auch! Denn Sie können das alles selbst erledigen.
Intuitive Benutzeroberfläche
Greifen Sie einfach auf in Hadoop gespeicherte Daten zu, transformieren und managen Sie diese mit einer Web-basierten Schnittstelle, die Schulungsanforderungen reduziert.
Speziell für das Laden von Daten auf oder von Hadoop entwickelt
Von Grund auf für das Management auf Hadoop entwickelt; nicht von vorhandenen IT-orientierten Tools umfunktioniert.
Verkettung und Zeitplanung von Direktiven
Mehrere zusammengefasste Direktiven können gleichzeitig oder nacheinander laufen. Die öffentlich freizugängliche API kann genutzt werden, um die Direktiven zeitlich festzulegen oder zu automatisieren.
Datenmanagement in Spark
Datenqualitätsfunktionen werden In-memory in Spark ausgeführt. Spark Matching und "Golden Record" ermöglichen Stammdatenmanagement für Big Data.
Qualität und Profiling von Big Data
Daten werden dank Direktiven, die Schreibweisen, Gender-Analysen, Musteranalysen und Feldextraktion beinhalten, und einer Profilerstellung, die zur Steigerung der Performance parallel im Hadoop-Cluster ausgeführt wird, genau und nutzbar.
In-Memory-Analytics-Server
Laden Sie Daten in den Arbeitsspeicher, um sie für leistungsstarkes Reporting, Visualisierungen oder Analysen vorzubereiten.
In-Cluster-Code und Durchführung von Datenqualitätsprojekten
Führen Sie in Hadoop Analysen und Datenqualitätsprozesse durch, um schnelle und kostengünstige Ergebnisse zu erhalten. Vermeiden Sie dabei die Verschiebung von Daten, um eine höhere Skalierbarkeit, Data Governance und Performance zu erreichen.
Integration von Big Data
Importieren Sie Daten als CSV oder in ähnlichen Formaten in Hadoop. Sie können außerdem HiveQL-Befehle ausführen und Zeilen in Hadoop-Tabellen löschen.
Mit SAS Data Loader for Hadoop können auch Sie im Fachbereich Ihre eigenen Daten ganz ohne Programmierkenntnisse managen.
Management von Daten ohne IT-Spezialwissen.
Nehmen Sie die Sache selbst in die Hand: Sie wissen, welche Informationen, Sie aus den Daten ziehen wollen und analysieren sie auch selbst. Der SAS Data Loader for Hadoop erleichtert Anwendern oder Data Scientists auch alle Aufgaben in der Vorbereitung einer Analyse. Meistern Sie die Herausforderungen von Datenintegrationen, Datenqualität und Datenvorbereitung ganz ohne ein komplexes MapReduce-Programm schreiben oder andere um Hilfe bitten zu müssen.
Für einfache Skalierung und höchste Performance.
Nie war Datenmanagement für den Fachbereich einfacher. Bereits erfahrene Data Scientists und SAS® Programmierer profitieren von gesteigerter Geschwindigkeit, Effizienz und Agilität. Dank eines Code-Beschleunigers können Codes im Hadoop-Cluster parallel und somit schneller ausgeführt werden. Zudem können Sie die Datenqualität verbessern, ohne Daten verschieben zu müssen: in Hadoop eingebette Datenqualitätsroutinen machen das möglich.
Machen Sie mehr aus Big Data.
Es ist viel einfacher als Sie denken, Daten von relationalen Datenquellen oder SAS Datenbestände auf und von Hadoop zu laden. Datenmanagement muss keine Hürde sein, um wirklich alle Daten voll auszunutzen. SAS unterstützt Sie mit bahnbrechenden Innovationen auf dem Weg zum datengetriebenen Unternehmen, das in einer digitalisierten Welt im Wettbewerb besteht.
Speed data management processes with Spark.
Data quality functions run in memory in Apache Spark for improved performance. Matching and best record creation enables master data management for big data. In addition, you can read and write to Spark data sets as needed.
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White Paper
Drive Next-Generation Customer Experiences with Real-Time Connected Product and Service Analytics SAS, Hortonworks and Intel can help you embrace technologies and processes to anticipate a wide range of customer needs, providing the foundation for next-generation customer experiences.
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Eight Considerations for Utilizing Big Data Analytics with HadoopThis paper focuses on eight considerations when it comes to applying big data analytics to extract value from Hadoop. Readers will learn about the importance of in-memory analytics, how to optimize the data preparation processes and the skill sets needed to derive benefits from Hadoop.
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White Paper
Improving Data Preparation for Business AnalyticsThis TDWI Best Practices Report discusses the latest data preparation processes, self-service options and how to effectively integrate data prep with analytics and BI solutions.r More Productive Users
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White Paper
A Non-Geek’s Big Data PlaybookThis paper examines how a non-geek yet technically savvy business professional can understand how to use Hadoop - and how it will impact enterprise data environments for years to come. The paper serves as a playbook that demonstrates six common “plays” that illustrate how Apache Hadoop can support and extend the enterprise data warehouse (EDW) ecosystem.
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White Paper
SAS and the Hadoop EcosystemA vendor profile from The Bloor Group that refers to the full report: Making Sense of Hadoop and its Ecosystem.
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Interview
Hadoop is the new boardroom buzzwordIn this Q&A, two Hadoop experts share what every executive needs to know.
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E-Book
An Early Adopter's Guide to HadoopRead interviews with two Hadoop customers and two Hadoop implementors, plus Hadoop adoption survey results and tips for big data management - all in one convenient ebook package.
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White Paper
Using Next-Generation Advanced Analytics to Harness Big DataDiscover why Heavy Reading recommends using advanced analytics from proven vendors to obtain real-time intelligence from all your big data.
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White Paper
Hadoop for the Enterprise: Making Data Management Massively Scalable, Agile, Feature-Rich, and Cost-EffectiveThis TDWI report accelerates users’ understanding of new products, technologies and best practices that have emerged around Hadoop. It will also help readers connect available options to use cases, with a focus on mainstream enterprise uses, while respecting proven IT practices and delivering maximum business value.
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Article
A Getting Started With Hadoop ChecklistFrom low-cost storage to distributed processing, Hadoop offers many promises. But there’s an expanding analytics ecosystem evolving around this big data platform that’s worth some study. Read our checklist and make sure you’re not overlooking anything important in your rush to get value from Hadoop.
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Improving Manufacturing Quality and Asset Performance With Industrial IoTDiscover how new real-time analytics approaches are driving next-generation manufacturing performance.
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Best Practices for Hadoop: A Guide From SAS CustomersEase your transition to Hadoop by following these tried-and-true best practices from SAS customers.
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SAS® and Apache Hadoop for Government This paper focuses on the integration of Hadoop-centric big data approaches with user-focused business analytics capabilities. Users see accessible business analytics tools that produce results, without the need for IT staff to craft queries in programming languages.
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Interview
The scoop on HadoopCloudera co-founder Mike Olson talks trends, changes and outlines the formula for success with Hadoop.
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Data Quality Challenges and PrioritiesFind out how organizations are addressing their most pressing data quality issues, discover the top 10 priorities for data quality solutions, and learn the best ways to engage and empower business users to improve data quality.
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The Current State of Hadoop in the EnterpriseWritten by the International Institute for Analytics, this paper presents a broad view of Hadoop in the marketplace, including how it is being adopted and used by global organizations. It then offers a set of recommendations that organizations can use to succeed with Hadoop.
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Webinar
How Do I Migrate Data From One Database Management System to Another?Learn best practices to migrate from one database management system to another.
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Making Sense of Hadoop and its EcosystemAn Investigation into the Evolution and Deployment of Hadoop
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How Hadoop Helps Realize Big Data ValueLeveraging a big-picture approach to Hadoop opens up a world of
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White Paper
Managing the Analytics Life Cycle for Decisions at ScaleLet the SAS Analytics Life Cycle guide you through the iterative process of going from raw data to predictive modeling to automated decisions, faster. This paper tells you how.
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Analyst Report
SAS throws its hat into the self-service data preparation ring with Data Loader for HadoopThe strategy centers on three key themes: 'big data'management and governance involving Hadoop, the streamlining of access to information, and the use of its federation and integration offerings to enable the right data to be available, at the right time.
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White Paper
Data Integration Déjà Vu: Big Data Reinvigorates DIDiscover why the latest evolution of data integration delivers more value from big data.
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Interview
How do you know if you’re ready for Hadoop?Ask an early adopter. Epsilon VP of Products answers our Hadoop questions about implementation, preparation and scalability.
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White Paper
Self-Service Big Data Preparation in the Age of Hadoop: A Conversation With SASLearn how SAS Data Loader for Hadoop enables business users – along with data scientists and IT – to access, profile, transform and cleanse Hadoop data. The best part is, it requires minimal training and no need for coding.
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White Paper
Bringing the Power of SAS to HadoopWant to get even more value from your Hadoop implementation? Learn about the SAS portfolio of solutions that enable you to bring the full power of business analytics to Hadoop.
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Analyst Report
Gartner positions SAS as a leader in the Magic Quadrant for Data Integration ToolsSAS is a leader in Gartner's Magic Quadrant for Data Integration Tools. Data integration from SAS helps you break down data silos and boost productivity.
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Webinar
Real-Time Connected Customer Experiences – Easier Than You ThinkGrowth in today’s hyper competitive marketplace is driving intense focus on digitally transforming the customer experience – and for good reason.
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White Paper
Understanding Big Data Quality for Maximum Information UsabilityDiscover why data quality and data governance are so important to large-scale analytics. Learn how to balance governance with usability so you can come up with a strategic plan for managing big data.
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