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As mentioned earlier, Audacity is a great DAW for podcasting beginners. It’s open source, free to use as long as you like, and is available for Windows, OS X, and Linux. Before you can jump into recording, however, there are a few tricks to getting it all set up properly: Download Audacity 2. Connect your microphone and open Audacity. See if your microphone is being recognized by Audacity by checking the drop- down menu next to the small microphone icon. If you see your mic, go ahead and select it. In the top- left corner, you should see the pause, play, stop, skip back, skip forward, and record buttons. Click the record button and talk into your mic to make sure it’s working properly. Stop recording and playback what you just recorded to make sure everything sounds okay. You’ll want to export your audio in the MP3 format later on. In order to do that, you’ll need to download and install the Lame MP3 encoder for either Windows or Mac. Once that’s installed, close and reopen Audacity. 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Als Standarddistribution kommt R mit einem Interpreter als Kommandozeilenumgebung mit rudimentären grafischen Schaltflächen. So ist R auf vielen Plattformen verfügbar; die Umgebung wird von den Entwicklern ausdrücklich ebenfalls als R bezeichnet. R ist Teil des GNU- Projekts. Zahlreiche, online abrufbare Pakete enthalten zusätzliche Funktionen, um Daten hinsichtlich Fragestellungen aus unterschiedlichen Fachbereichen zu analysieren; weitere eigene Funktionen können erstellt werden. Die Sprache bietet Schnittstellen zu anderen Programmiersprachen und Möglichkeiten zur Integration in verschiedene Software. R grenzt sich in mehrerer Hinsicht von anderen bekannten Statistik- Umgebungen ab und kann nicht ausschließlich als Statistiksoftware bezeichnet werden. Obwohl andere, heutzutage mit grafischen Benutzeroberflächen versehene Statistik- Umgebungen wie SPSS ebenfalls als spezialisierte Programmiersprachen begannen (und diese Fähigkeit bis heute beibehalten), fokussiert sich R auf seine Stärke als Statistik- orientierte Programmiersprache. R grenzt sich von anderen Programmiersprachen durch die für Statistik entworfenen Datenstrukturen und Funktionen sowie die Möglichkeiten bei der Grafikerzeugung ab. Nachteilig an R ist die niedrige Geschwindigkeit. R gilt zunehmend als die Standardsprache für statistische Problemstellungen sowohl in der Wirtschaft als auch in der Wissenschaft.[1][2][3][4][5] Im TIOBE- Index belegt R Platz 1. Ranking von Red. Monk Platz 1. PYPL Platz 9[8] und beim Institute of Electrical and Electronics Engineers Platz 5.[9]R wurde 1. Statistikern Ross Ihaka und Robert Gentleman an der Universität Auckland entwickelt. Sie orientierten sich dabei eng an der in den Bell Laboratories (heute Teil von Alcatel- Lucent und somit Nokia) entwickelten Sprache S, die zur Verarbeitung statistischer Daten dient. R kann als freie Implementierung von S angesehen werden. Daher ist die Mehrzahl der für S geschriebenen Programme unter R lauffähig. Der Name der Sprache ist auf den Anfangsbuchstaben der Vornamen der Entwickler zurückzuführen und zudem in Anlehnung an S entstanden.[1. S hatte eine andere Herangehensweise als bisherige Software für Statistik. Mit S konnten Daten schneller explorativ untersucht werden und passende Grafiken erstellt werden, während Analysefunktionen zu Beginn der 1. Jahre noch nicht umfangreich implementiert waren.[1. Das Unternehmen Statistical Sciences, Inc. Lizenz für die Verbreitung von S- Software ab 1. Ihaka und Gentleman mochten die Herangehensweise und Möglichkeiten, die S für statistische Fragestellungen bot (damalige Version: S3). Sie bemängelten die Scoping- Fähigkeiten von S, bei denen klar zwischen lokalen und globalen Variablen unterschieden wurde und insbesondere die Speicherverwaltung, die ohne Garbage Collection zu schnellem Anwachsen des dynamischen Speichers führte. Sie wollten diese Eigenschaften in ihren Forschungsprojekten nutzen und zudem schneller und flexibler neue analytische Verfahren implementieren, ohne auf die S- Entwickler angewiesen zu sein. Daher erschufen sie R. Ein weiterer Vorteil war der verfügbare Quelltext, sodass sie R anschaulich für Lehrzwecke an der Universität einsetzen konnten.[1. Die Entwickler schrieben zuerst einen Interpreter für Scheme und wandelten die Sprache soweit ab, dass sie S ähnelte. Die Programmierung von R fand in C (sogenannte primitive Funktionen), Fortran (zum Beispiel BLAS und LAPACK für numerische lineare Algebra) und darauf aufbauend in R selbst statt. Vor wenigen Jahren bestand der Quelltext der Standardbibliothek zu 2. R- Code, während 5. Programmzeilen in C und Fortran geschrieben waren.[1. Sprache erstmals öffentlich verbreitet: Die Designer luden Binärdateien ihrer bisherigen Arbeit in der Sektion Stat. Lib der Carnegie Mellon University hoch, welches eine Sammelstelle und ein Distributionskanal für statistische Software war und erhofften sich Feedback. Zudem gab es separate Bekanntmachungen an Personen, die sich enger mit S befassten. Martin Mächler von der ETH Zürich war einer der Feedbackgebenden. Er ermunterte Ihaka und Gentleman zudem zur freien Distribution von R sodass die Sprache seit Juni 1. GNU General Public License steht.[1. Bis 1. 99. 6 oder 1. Leute in einer Mailingliste, die dabei halfen die Sprache gemeinsam zu verbessern.[1. Einige nutzen das zeitgleich sich verbreitende Linux, wofür R die einzige Statistikumgebung war.[1. Im Jahr 1. 99. 7 wurde das R Development Core Team gebildet (heute R Core Team), das sich um die Weiterentwicklung von R kümmert und den Quellcode verändern kann. Mittlerweile zählen zwanzig Personen zu diesem engsten Entwicklerteam um Ross Ihaka und Robert Gentleman. Das Comprehensive R Archive Network(CRAN) als Plattform für Pakete startete am 2. April 1. 99. 7 um Anwendern die Möglichkeit zu geben selbst geschriebene Funktionen leichter mit Anderen zu teilen. Der älteste öffentlich verfügbare Quelltext für Unixoide fällt auf dieses Datum; die Alpha- Versionen für Microsoft Windows und Mac erschienen kurze Zeit später. Am 2. 9. Februar 2. R Development Core Team als stabil betrachtete Version 1. Seit April 2. 00. R für mac. OS. Im September 2. Mitglieder des R Development Core Teams den gemeinnützigen Verein The R Foundation for Statistical Computing in Wien, welcher sich um die Außendarstellung kümmert. Die R- Version 2. Oktober 2. 00. 4 veröffentlicht. Seitdem nutzt R Lazy Loading, um Daten bei geringer Beanspruchung des Arbeitsspeichers schnell laden zu können. Ab Version 2. 1 (1. April 2. 00. 5) unterstützt R unterschiedliche Sprachversionen (Internationalisierung) und Zeichenkodierungen, insbesondere UTF- 8. In der Folge gab es einige Verbesserung der Performance. Dazu zählt die Einführung von Version 2. April 2. 01. 0, die R auf 6. Bit- Systemen nutzbar macht und bis zu acht Terabyte Arbeitsspeicher adressieren kann. Zusätzlich erschien mit der Version 2. Paket compiler, welches in R geschriebene Funktionen zu Bytecode kompilieren kann und einen Just- in- Time- Compiler enthält; mittlerweile sind die bereits existierenden, nicht vom Benutzer geschriebenen Funktionen bereits als Bytecode vorhanden. Zudem wurde im Oktober 2. Version 2. 1. 4) grobkörnige Nebenläufigkeit für parallele Ausführung von Funktionen eingeführt. Ab Version 3. 0 (April 2. Indexwerte von 2. Bit- Systemen möglich.[1. Die Versionsnummern von R bestehen klassisch aus drei durch Punkte getrennte Zahlen. Fundamentale Veränderungen werden durch eine Erhöhung der ersten Zahl sichtbar, normale durch eine Erhöhung der zweiten Zahl. Die dritte Zahl wird bei neuen Versionen erhöht, die vorwiegend der Behebung von Bugs dienen. Seit R- Version 2. Version einen unterhaltsamen Namen. Die Namensgebung ist unsystematisch, jedoch wurden einige Namen passend zu jahreszeitlichen Ereignissen gewählt. Die am 2. 1. Juni 2. Version 3. 3. 1 heißt Bug in Your Hair.[2. Versionsnummer. Erscheinungsdatum. Bezeichnung. Kommentar 0. Start von CRAN, erste öffentliche Unix- Version von R (Paket base)0. Möglichkeit Pakete aus R heraus von CRAN zu installieren. Hinzufügung des Pakets splines für glättende Regressions- Splines und interpolierende Splines. Entwicklern als stabil betrachtete Version. Hinzufügung des Pakets tcltk um auf das Tk- Toolkit zur Erstellung von grafischen Benutzeroberflächen zugreifen zu können. Speicherverwaltungssystem mit generationellem Garbage Collector. Version für mac. OS1. Hinzufügung der Pakete methods, welches S4- Methoden bereitstellt, und tools zur Paketentwicklung und - verwaltung. Hinzufügung des Pakets grid für bessere Steuerung der Position von Grafiken in Output- Dateien. Pakete graphics (Grafiken), stats (Statistik- Funktionen) und utils (Programmier- und Entwicklerwerkzeuge) lösen sich aus dem Paket base (wichtigste R- Funktionen); die bisherigen Pakete ctest, eda, modreg, mva, nls, stepfun und ts werden ins neu geschaffene Paket stats verschoben, mle ins neu geschaffene Paket stats. Funktionen für S4- Klassen); lqs ist nur noch empfohlener Bestandteil der Standardbibliothek. Unterstützung von Lazy Loading; das Paket gr. Devices löst sich aus graphics um den Schritt der Datenvisualisierung von der Output- Datei zu trennen; Hinzufügung des Pakets datasets, welches Beispieldatensätze enthält. Cognos Webinars, Demos, White Papers, Presentations, Hints. IBM Cognos Business Intelligence version 1. This webinar highlights the latest and greatest offerings, including the Report Studio preview modes making authoring for Active Report and other mobile consumers much less cumbersome. Our special guests Stefan Constantinides, Solution Advisor North America for IBM, and Don Davis, Client Technical Professional in Business Analytics for IBM, also demonstrate and discuss: Simplified end- user functionality for greater user self- service. Simplified deployment for faster time to value. Numerous improvements in general data access and administration. Additionally, we touch on Cognos Disclosure Management (CDM), which can be a huge time saver when generating reports, along with Watson Analytics. Get up to speed on what the latest version of Cognos BI offers. PRESENTERStefan Constantinides. Solution Advisor North America. IBMStefan Constantinides has Expert level certification within IBM as a Solution Advisor and technical pre- sales solution architect. Over the course of his career, Stefan has had successful sales engagements with companies like Amazon, Disney, Wells Fargo, Sprint, Charles Schwab, AT& T and many other large, high profile accounts. With over 6 years at IBM and almost 3 decades of enterprise level experience, Stefan is now working with large companies to ensure their success with IBM products and helping to guide their business into the future. Don Davis. Client Technical Professional - Business Analytics. IBMDon Davis is a Client Technical Professional in IBM's Business Analytics software group, residing in the Seattle area. Don has been helping clients with Cognos BI since 2. OUTLINEWhat’s New in Cognos BI Version 1. Added Features and Functionalities Overview. Enabling Foundational Self- Service with Cognos Business Intelligence V1. Speed deployment to enable foundational self- service. Targeted profiles will engage even more users and make them more self- sufficient. Customize profiles in Report Studio and Workspace Advanced. Views based on skill and required functionality. Enables more users to be self- sufficient. Use ‘quick set- up’ to easily install and configure all Cognos BI components for testing and prototyping. Increase confidence by managing security at the individual user level in multi- tenant deployments. Leverage high performing Dynamic Cubes by quickly migrating existing Framework Manager models. Proactively plan your upgrade using the Cube Designer hardware sizing guide. Support users with a broad range of disabilities with broadened accessibility. US Section 5. 08 Compliant, from modeling through to authoring. Supports assistive technologies. Produce fully accessible, compliant reports. Streamline the report creation process to save time and make authors more efficient. Build a report once and create a consistent corporate identity with reusable style templates. Define styles for standardized reporting. Create templates for groups to provide a starting point. Simplify report maintenance by updating styles once. Leverage the new visualization capabilities and customize them directly in Report Studio. Extensible visualization properties are exposed in Report Studio and Workspace Advanced. Extensible visualization data slots are now flexible, use only those that you need. See changes to your reports in real- time and speed authoring with Active Report Live Preview. View Active Report Content in Report Studio Directly. Change Layout to Match Device Output or Custom. Make Formatting Changes Directly in Preview Mode. Empower more users with increased personalization and targeted capabilities. Quickly upload and easily model personal data sources for end- to- end analysis with My Data Sets. Upload CSV, XLS, XLSX, and create reports and dashboards. Manage uploaded data files without ITAdministrators can define who has privileges. Quickly focus your analysis by using Dynamic Filters in Cognos Workspace. Create interactive dashboards for easy analysis. Define custom buttons that specify a filter action. Filter related widgets by selecting values. Learn more about these exciting innovations on Analytics. Zone IBM Watson Analytics and Cognos Business Intelligence. Cloud- based agile analytics for business users. Guided flexible exploration with cognitive computing and automated visualization selection. Automated discovery of combinations and permutations of data providing new answers. A standardized gateway to maximize business intelligence value across the Enterprise. Foundational business intelligence for the enterprise. Support for multiple data sources and operating environments with customizable visualizations. A known and trusted analytics foundation. Provides a baseline of information to feed Watson Analytics across one integrated and supported environment. Demonstrations Cognos 1. Cognos Disclosure Management (CDM) Introduction. CDM Deployed at Amazon: HUGE time saver. Now with using CDM, it takes five minutes to generate the monthly executive level report that used to take a minimum of 3 hours to cobble together. CDM is rapidly becoming irreplaceable at Amazon. One of the Amazon team described it as something as essential as turning the lights on. How? Specific and underlying reporting problems. The “Do it Again” Problem. Every month means all reports need to be updated to reflect the current period. Title pages. Date references in text. Narrative comments. Dates that drive the data reported. Data reported. How IBM Cognos Disclosure Management (CDM) addresses the problems. Leverages existing tools in use; Word, Excel, etc. Reports directly integrated with data sources so they can be rolled forward; Master documents can be cascaded. Changes dynamically updated in reports, e. Provides a powerful multi- user, collaborative environment. Workflow and version controls deliver process transparency. Evidence of compliance, report validation, access control and audit trails reduce operational risk. Reports driven from a single, secure database so stakeholders and consumers get a consistent view. Multiple output formats. Integrated XBRL taxonomy, XBRL validation and pre- tagged template reports. Organizations are relying on outdated tools and processes to meet mandated reporting requirements. Abundance of reports and changing requirements. Manual time- consuming processes. High Risk of errors. What we deliver. Employ a repeatable process. Instead of navigating gaps in the production of recurring reports over and over again. Streamline report assembly. Instead of manually piecing together Microsoft Word, Excel and Power. Point files. Make better decisions. Instead of interpreting “just read” data, get to understanding right away. Recurring, multi- author reports create the same problems. Time is spent on low- value work (data/text, copy/paste, editing, validation)Limited time for specialists to make insightful decisions. Slow, manual, recurring process. Facts within reports can be out of date before the report even published. No compliance or controls during the process. Cognos Disclosure Management (CDM) solution features. Replace tools and manual processes with a proven reporting solution used by 3. Filing packages provide all the templates and XBRL connectivity that you need. Familiar MS Office interface for ease of use. Reduce the risk of errors with strong data integration. Built in workflow plus full audit trail provides visibility and transparency. Reports cascading for easier reporting of multiple subsidiaries. Rollover capabilities reduce reporting for future cycles and provide an easy transition between periods and mandate versions. Questions: What’s New in Cognos BI Version 1. The following questions were originally collected during the live webinar session and answered by the Senturus team. You can download the complete Questions Log from the right hand side bar at the top of this page. Questions. Q: Just looking at the 1. Framework Manager and Report Studio capabilities. However, I only see TM1 and Business Insight as actual 1. IBM site under Software Catalog. Is there actually a Framework Manager 1. Report Studio 1. 0. Can you go over the actual products that were updated, and if not, what their packages may be (i. Framework Manager 1. TM1 1. 0. 2. 2) or other actual updated mix & matches to install to get the updates claimed in the videos? Q: Will the IBM Cognos quick setup be available for SQL server in the future? Q: Will the tenant capabilities be called out in the licenses? Q: Do I have to get 1. |
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November 2017
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