Oversikt over relevante kurs innen Big Data i Akershus

Data genereres i stadig større mengder - av mennesker, av sensorer og av innebygde dataenheter. Mottak, behandling og analyse av store datamengder krever distribuerte teknologier og lagringsformater. Big Data er blitt et fellesbegrep på disse teknologiene og dataene de behandler. Det er i dag forretningskritisk innenfor flere og flere bransjer å kunne håndtere Big Data. Men hvor skal man begynne? Kursinnhold Hvordan defineres Big Data? Hvilke problemstillinger kan løses med Big Data Hvilke Big Data teknologier finnes og hvilke bør vi satse på? Hva er hovedutfordringene med å ta i bruk Big Data? Kurset gjennomføres som en serie foredrag med rom for spørsmål og utdypninger innen hvert emne. De mest brukte teknologiene innen Big Data lagring, datahåndtering og analyse blir gjennomgått og vurdert, inkludert Hadoop, Spark, Hive, HBase, Cassandra, Kafka, MongoDB og en rekke andre. [-]

  Dave Wells: Practice Director, Data Management at Eckerson Group    Dave Wells is an advisory consultant, educator, and industry analyst dedicated to building meaningful connections throughout the path from data to business value. More than forty years of information systems experience combined with over ten years of business management give him a unique perspective about the connections among business, information, data, and technology.   Managing data in an analytics- driven organization is complex and challenging. Abundant data sources, variety of data types, and multiple use cases result in many data pipelines—possibly as many as one distinct pipeline for each use case. Capabilities to find data, manage dataflow and workflow, and deliver the right data in the right forms for analysis are essential for all who seek to become analytics-driven organizations.    Multiple and complex data pipelines quickly become chaotic with pressures of agile, democratization, self-service, and organizational “pockets” of analytics. Increased difficulty of governance and uncertainty of data usage are only the beginning. From enterprise BI to self-service analysis, data pipeline management should ensure that data analysis results are traceable, reproducible, and of production strength. Robust pipeline management works across a variety of platforms from relational to Hadoop, and recognizes today’s bi-directional data flows where any data store may function in both source and target roles.    You Will Learn:    •The challenges and complexities of modern data pipelines •Why dataflow and workflow are critical parts of analytics architecture and how they fit into architecture •The roles and functions of metadata in pipeline management •The important relationships of pipeline management and data governance •How to define and design data pipelines •The state of tools and technologies to support pipeline management    OM CGI   CGI Group Inc. ble grunnlagt i 1976 og er verdens femte største uavhengige leverandør av tjenester innen IT- og forretningsprosesser. Med 74 000 medarbeidere over hele verden, leverer CGI en portefølje av ende-til-ende løsninger innen avanserte IT- og forretningskonsulenttjenester, systemintegrasjon og utsetting av IT- og forretningsprosesser. CGIs modell med kundenærhet, et globalt leveransenettverk og egne løsninger bidrar til at kundene hurtigere oppnår resultater og bidrar til deres digitale transformasjon. CGI har en samlet årlig omsetning på over 60 milliarder NOK. CGI-aksjene er notert på TSX (GIB.A) og NYSE (GIB). Hjemmeside: www.cginorge.no    [-]

About this course The main purpose of the course is to give students a good understanding of data analysis with Power BI. The course includes creating visualizations, the Power BI Service, and the Power BI Mobile App.   Audience profile The course will likely be attended by SQL Server report creators who are interested in alternative methods of presenting data.   At course completion After completing this course, students will be able to: Perform Power BI desktop data transformation. Describe Power BI desktop modelling. Create a Power BI desktop visualization. Implement the Power BI service. Describe how to connect to Excel data. Describe how to collaborate with Power BI data. Connect directly to data stores. Describe the Power BI developer API. Describe the Power BI mobile app.   Certifisering This course prepares you for exam 70-778, and is a prerequisite for MCSA BI Reporting Certification.   Course Prerequisites The course suits you who want to analyze large datasets in a big data environment, o if you are a developer and want to integrate R analyzes into solutions.     [-]

About this course The main purpose of the course is to give students the ability to use Microsoft R Server to create and run an analysis on a large dataset, and show how to utilize it in Big Data environments, such as a Hadoop or Spark cluster, or a SQL Server database.   Audience profile    The primary audience for this course is people who wish to analyze large datasets within a big data environment. The secondary audience are developers who need to integrate R analyses into their solutions.   At course completion After completing this course, students will be able to: Explain how Microsoft R Server and Microsoft R Client work Use R Client with R Server to explore big data held in different data stores Visualize data by using graphs and plots Transform and clean big data sets Implement options for splitting analysis jobs into parallel tasks  Build and evaluate regression models generated from big data  Create, score, and deploy partitioning models generated from big data Use R in the SQL Server and Hadoop environments     Certifications This course prepares you for exam 70-773, and is a prerequisite for MCSA Machine Learning Certification.   Prerequisites The course suits you who want to analyze large datasets in a big data environment, or if you are developers and want to integrate R analyzes into their solutions.   [-]