Big Data – fra buzzword til brugbart værktøj
Der findes en række værktøjer til at arbejde med Big Data. Mange af de værktøjer er open source og Linux distribution baseret. Arbejdet med Big Data kræver en holistisk tilgang og en ændring i de almindelige arbejdsgange. Kursussamlingen dækker de grundlæggende principper ved Big Data, herunder dets placering i en IT-historisk kontekst og tilgængelige værktøjer til at arbejde med Big Data. Derudover lærer du om, hvordan teams arbejder i organisationer med Big Data projekter og use cases samt om nogle af de udfordringer og muligheder, som der findes ved Big Data.
Du lærer at bruge nøgleværktøjerne til arbejdet med Big Data såsom Apache Spark, Apache Hadoop, MapReduce, og Apache Kafka. Endeligt dækker kursuspakken forskellige perspektiver på Big Data såsom lederskab, engineering, juridisk, markedsføring og salg.
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Kursussamlingen henvender sig til IT-ingeniører, programmører og databaseadministratorer, der enten arbejder med eller er interesserede i Big Data såvel som forretningsmæssige beslutningstagere, som er interesserede i at implementere eller administrere Big Data-systemer.
Udbytte
Du lærer blandt andet:
- Det seneste inden for Big Data teknologier fra førende eksperter.
- Big Data i et supercomputing perspektiv.
- Big Data i kontekst med teknologibølger – samt Big Data i forhold til og sammenlignet med tidligere bølger af teknologi.
- Om de faktorer, som har indflydelse på Big Data teams.
- Hvordan Big Data produkter er økonomiske motorer.
- At sammenligne building vs. buying-tilgange til Big Data færdigheder.
- At sammenligne fordele og ulemper ved at bygge en in-house Big Data-infrastruktur.
- Forhold i forbindelse med fortrolige oplysninger.
- Hvordan Big Data kan anvendes i marketing.
Indhold
Big Data Fundamentals (2 courses)These courses covers the fundamentals of Big Data, including positioning it in a historical IT context, the tools available for working with Big Data, the Big Data stack, and finally an overview of Big Data opportunities and challenges.
Apache Spark Fundamentals (1 course)In this course, you will learn how to develop Spark applications using Scala, Java, or Python. You will also learn how to test and deploy applications to a cluster, monitor clusters and applications, and schedule resources for clusters and individual applications.
Apache Hadoop and MapReduce Essentials (2 courses)These courses will introduce the basic concepts of cloud computing using Apache Hadoop, cloud computing, Big Data, and the development tools applied, and explore MapReduce programming and explain the basics of programming in MapReduce and Hive.
Hadoop Ecosystem (10 courses)These courses examine the Hadoop ecosystem by demonstrating all of the commonly used open source software components. You will explore installation of Hadoop, and various data repositories, data refinery, data factories, and finally the data flow for the Hadoop ecosystem.
Hadoop Operations (10 courses)In these courses you will learn about the design principles, the cluster architecture, considerations for servers and operating systems, and how to plan for a deployment. Furthermore you will explore the use of clusters.
Big Data - The Marketing Perspective (1 course)In this course we will examine the impacts of big data from the marketing perspective. We will look at how the mobile effect has changed marketing, how purchasing habits have changed and what impact datafying consumer behavior has done.
Apache Spark Advanced Topics (3 courses)In these courses, you will learn how to improve Spark's performance and work with Data Frames, Spark SQL, Spark Core, Spark Streaming, and MLlib, GraphX, and R.
Apache Kafka (2 courses)These courses covers the basic concepts of Apache Kafka, and considerations for deploying Kafka and managing servers, as well as Apache Kafka Development.
Apache Storm Introduction (2 courses)These courses will introduce Storm providing an in depth approach to the concepts and how Apache Storm ticks. Apache Storm can integrate with many other products and this course will introduce you to ZooKeeper along with the Storm Trident Architecture and how they are used with Storm model. Also, you will be introduced to Trident and its relationship to Storm, along with its integration. Many other integrations will be explored including Hadoop, Kafka, JMX, Ganglia, and even automation using Puppet as well as monitoring and analytics tools. In this course, you will also learn how to deploy the Storm architecture.
IBM BigInsights Fundamentals (2)In these courses, you will be introduced to the fundamentals of IBM BigInsights Apache Hadoop, including its components, features, benefits, capabilities, and the architecture of IBM BigInsights Hadoop. You will also learn how to use BigSheets to analyze data, how to use Big SQL to query and analyze data, and analyze data using BigInsights Text Analytics. The course also covers using Big R to analyze data.
Apache Solr Essentials (2 courses)These courses focuses on the deployment of the Apache service, the configuration of its core service components, and techniques used to import data, and to manage/manipulate data during import to the Solr index. Through discussion and demonstration, these courses focuses on searching or querying a Solr collection – including search parameters and faceted search techniques. In addition, the courses covers data management, importing data from a structured data source, and the deployment of the SolrCloud service.
Big Data Operations (2 courses)These courses cover the types of challenges being faced day to day by rethinking data systems from the ground up. The courses also covers in-depth topics such as monitoring tools, orchestrations, and performance modeling. In these courses, you'll learn about big data testing and challenges that organizations face with big data operations.
Data Modeling for Hadoop (2 courses)These courses will introduce Hadoop, and its key tools and their applications and cover various data genres and management tools, the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems, and analytical tools.
Designing and Implementing Big Data Analytics (7 courses)These courses cover data ingesting and storage and designing and provisioning compute clusters, and cover batch processing technologies and data security tools in Azure. The courses cover data ingesting and designing compute resources for real-time processing as well as the Lambda architecture and Azure Stream Analytics. The courses cover the provisioning of the components of an Azure Data Factory and implementation of data processing activities in a data-driven workflow. They cover monitoring the Azure Data Factory and troubleshooting problems as well as loading and transforming data and cover the automation of key tasks using Azure PowerShell and key capabilities of Azure Machine Learning for big data analysis.
Big Data Development with Apache SparkIn these course, you will be introduced to Apache Spark. You'll learn how to download and install Apache Spark, and you'll also learn how to build, configure, and initialize Spark. In the courses, you will be introduced to Apache Spark SQL, Datasets, and DataFrames and you will learn about the concepts of Structured Steaming such as Windowing, DataFrame, and SQL Operations. You will also learn about File Sinks, Deduplication, and Checkpointing. In these courses, you will learn about various ways to monitor Spark applications such as web UIs, metrics, and other monitoring tools. You will also learn about memory tuning. The courses introduce Spark security and you will learn about securing Spark UI, event logs, and configuring SSL settings. You will also learn about YARN deployments, SASL encryption, and network security.
Tidsforbrug
Kursuspakken består af 62 kurser, hvor hvert kursus gennemsnitligt varer omkring to timer. Hele kursuspakken kan således gennemføres på ca. 114 timer.
Form
Denne online kursuspakke består af flere forskellige kurser, som du ved tilmelding har adgang til i 365 dage. Hvert enkelt kursus er opdelt i flere kursusmoduler, som du via en oversigtsmenu kan tage i den rækkefølge, du ønsker. Modulerne indeholder lyd, billeder og tekst, der gennemgår kursusindholdet. Nogle moduler indeholder små videofilm med scenarier og cases. Ved hvert kursus har du mulighed for at teste din forståelse af indholdet med tests, som du kan tage både før, under og efter kurset. Du gennemfører kursusmodulerne via din computer eller tablet med lyd og adgang til Internettet. Du kan selv styre, hvornår du vil tage modulerne – og de kan sættes på pause undervejs. Der bliver indsat bogmærker, der hvor du er nået til, så du altid har mulighed for at fortsætte, hvor du sidst kom til.
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