商業智能培訓 | Business Intelligence培訓

  1. 培訓項目
  2. Data Analysis培訓
  3. 商業智能培訓 | Business Intelligence培訓
商業智能培訓

本地，有指導性的實時商業智能（BI）培訓課程通過實踐練習來演示如何理解，規劃和實施組織內的商務智能。 BI培訓可作為“現場實況培訓”或“遠程實時培訓”。現場實地培訓可在當地客戶所在地進行台灣或者在NobleProg公司的培訓中心台灣 。遠程實時培訓通過交互式遠程桌面進行。 NobleProg您當地的培訓提供商。

Machine Translated

客戶評論

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商業智能子類別

Power BI培訓Power BI
Tableau培訓Tableau
JasperReports培訓JasperReports
Apache Superset培訓Apache Superset
MicroStrategy培訓MicroStrategy
Splunk培訓Splunk
Apache Druid培訓Apache Druid
Dashbuilder培訓Dashbuilder
SAS培訓SAS
Stata培訓Stata
Alteryx培訓Alteryx
IBM Cognos培訓IBM Cognos
Google Sheets培訓Google Sheets
QlikView培訓QlikView
Metabase培訓Metabase
Redash培訓Redash
Pentaho培訓Pentaho

商業智能課程大綱

課程名稱
課程時長
概觀
課程名稱
課程時長
概觀

Sisense Business Intelligence

14小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at developers and system administrators who wish to learn and use Sisense for big data manipulation and visualization. By the end of this training, participants will be able to:
  • Learn the fundamental concepts of Sisense and how it works.
  • Create a Sisense dashboard to visualize big data and execute data-driven business decisions.
  • Merge and manage data from multiple sources.
  • Utilize Sisense for quick data manipulation and visualization.

AWS QuickSight

14小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at data analysts or anyone who wishes to use AWS QuickSight data analysis and visualization. By the end of this training, participants will be able to:
  • Understand the basic concepts of AWS QuickSight.
  • Use AWS QuickSight to create data analysis, reports, and insights.
  • Use AWS to create relationships between data for enhanced analysis.
  • Learn different types of visualizations in understanding data.

Data Analysis with SQL, Python, and Tableau

14小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at data scientists and developers who wish to use and integrate SQL, Python, and Tableau to perform complex data analysis, processing, and visualization. By the end of this training, participants will be able to:
  • Set up the necessary environment to perform data analysis with SQL, Python, and Tableau.
  • Understand the key concepts of software integration (data, servers, clients, APIs, endpoints, etc.).
  • Get a refresher on the fundamentals of Python and SQL.
  • Perform data pre-processing techniques in Python.
  • Learn how to connect Python and SQL for data analysis.
  • Create insightful data visualizations and charts with Tableau.

Alteryx Advanced

14小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at data scientists and data analysts who wish to learn how to use each tool in the developer tool palette in Alteryx Designer. By the end of this training, participants will be able to:
  • Learn to use and configure all the tools in the developer tab.
  • Design efficient workflows in Alteryx using the dynamic, validation, and testing tools.
  • Learn how to use API tools to download and parse web data.
  • Use Alteryx scripting tools, including Python and R.

Excel to Power BI

7小時
Microsoft Excel是世界上最受歡迎的業務分析，報告和策略軟件。 Power BI是一種商業智能工具，用於在業務運營級別可視化數據。 這種由講師指導的實時培訓（現場或遠程）針對希望學習Excel數據準備技術，然後在Power BI中將其可視化的數據分析人員。 在培訓結束時，參與者將能夠：
  • 了解數據分析的原理，數據分析的目標以及數據分析的方法。
  • 在Power BI使用DAX公式進行複雜的計算。
  • 為特定的分析案例創建和使用可視化和圖表。
  • 使用Power View導入，可以從基於Excel的Power BI遷移到獨立的Power BI 。
課程形式
  • 互動式講座和討論。
  • 很多練習和練習。
  • 在現場實驗室環境中動手實施。
課程自定義選項
  • 要請求此課程的定制培訓，請與我們聯繫安排。

Datameer for Data Analysts

14小時
Datameer是基于Hadoop構建的商業智能和分析平台。它允許最終用戶以易用的方式訪問，探索和關聯大規模，結構化，半結構化和非結構化數據。 在這個有指導意義的實時培訓中，參與者將學習如何使用Datameer來克服Hadoop陡峭的學習曲線，因爲他們將逐步完成對一系列大數據源的設置和分析。 在培訓結束後，參與者將能夠： 創建，策劃和交互式地探索企業數據湖訪問商業智能數據倉庫，交易數據庫和其他分析商店使用電子表格用戶界面設計端對端數據處理管道訪問預建功能來探索複雜的數據關系使用拖放式向導來可視化數據並創建儀表板使用表格，圖表，圖形和地圖來分析查詢結果 聽衆 數據分析師 課程的格式 部分講座，部分討論，練習和沈重的練習

Business Intelligence in MS SQL Server 2008

14小時
Training is dedicated to the basics of create a data warehouse environment based on MS SQL Server 2008. Course participant gain the basis for the design and construction of a data warehouse that runs on MS SQL Server 2008. Gain knowledge of how to build a simple ETL process based on the SSIS and then design and implement a data cube using SSAS. The participant will be able to manage OLAP database: create and delete database OLAP Processing a partition changes on-line. The participant will acquire knowledge of scripting XML / A and MDX.

Big Data Business Intelligence for Govt. Agencies

35小時
Advances in technologies and the increasing amount of information are transforming how business is conducted in many industries, including government. Government data generation and digital archiving rates are on the rise due to the rapid growth of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As digital information expands and becomes more complex, information management, processing, storage, security, and disposition become more complex as well. New capture, search, discovery, and analysis tools are helping organizations gain insights from their unstructured data. The government market is at a tipping point, realizing that information is a strategic asset, and government needs to protect, leverage, and analyze both structured and unstructured information to better serve and meet mission requirements. As government leaders strive to evolve data-driven organizations to successfully accomplish mission, they are laying the groundwork to correlate dependencies across events, people, processes, and information. High-value government solutions will be created from a mashup of the most disruptive technologies:
  • Mobile devices and applications
  • Cloud services
  • Social business technologies and networking
  • Big Data and analytics
IDC predicts that by 2020, the IT industry will reach $5 trillion, approximately $1.7 trillion larger than today, and that 80% of the industry's growth will be driven by these 3rd Platform technologies. In the long term, these technologies will be key tools for dealing with the complexity of increased digital information. Big Data is one of the intelligent industry solutions and allows government to make better decisions by taking action based on patterns revealed by analyzing large volumes of data — related and unrelated, structured and unstructured. But accomplishing these feats takes far more than simply accumulating massive quantities of data.“Making sense of thesevolumes of Big Datarequires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information,” Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a post on the OSTP Blog. The White House took a step toward helping agencies find these technologies when it established the National Big Data Research and Development Initiative in 2012. The initiative included more than $200 million to make the most of the explosion of Big Data and the tools needed to analyze it. The challenges that Big Data poses are nearly as daunting as its promise is encouraging. Storing data efficiently is one of these challenges. As always, budgets are tight, so agencies must minimize the per-megabyte price of storage and keep the data within easy access so that users can get it when they want it and how they need it. Backing up massive quantities of data heightens the challenge. Analyzing the data effectively is another major challenge. Many agencies employ commercial tools that enable them to sift through the mountains of data, spotting trends that can help them operate more efficiently. (A recent study by MeriTalk found that federal IT executives think Big Data could help agencies save more than $500 billion while also fulfilling mission objectives.). Custom-developed Big Data tools also are allowing agencies to address the need to analyze their data. For example, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. The system has helped medical researchers find a link that can alert doctors to aortic aneurysms before they strike. It’s also used for more mundane tasks, such as sifting through résumés to connect job candidates with hiring managers.

Big Data Business Intelligence for Telecom and Communication Service Providers

35小時
Overview Communications service providers (CSP) are facing pressure to reduce costs and maximize average revenue per user (ARPU), while ensuring an excellent customer experience, but data volumes keep growing. Global mobile data traffic will grow at a compound annual growth rate (CAGR) of 78 percent to 2016, reaching 10.8 exabytes per month. Meanwhile, CSPs are generating large volumes of data, including call detail records (CDR), network data and customer data. Companies that fully exploit this data gain a competitive edge. According to a recent survey by The Economist Intelligence Unit, companies that use data-directed decision-making enjoy a 5-6% boost in productivity. Yet 53% of companies leverage only half of their valuable data, and one-fourth of respondents noted that vast quantities of useful data go untapped. The data volumes are so high that manual analysis is impossible, and most legacy software systems can’t keep up, resulting in valuable data being discarded or ignored. With Big Data & Analytics’ high-speed, scalable big data software, CSPs can mine all their data for better decision making in less time. Different Big Data products and techniques provide an end-to-end software platform for collecting, preparing, analyzing and presenting insights from big data. Application areas include network performance monitoring, fraud detection, customer churn detection and credit risk analysis. Big Data & Analytics products scale to handle terabytes of data but implementation of such tools need new kind of cloud based database system like Hadoop or massive scale parallel computing processor ( KPU etc.) This course work on Big Data BI for Telco covers all the emerging new areas in which CSPs are investing for productivity gain and opening up new business revenue stream. The course will provide a complete 360 degree over view of Big Data BI in Telco so that decision makers and managers can have a very wide and comprehensive overview of possibilities of Big Data BI in Telco for productivity and revenue gain. Course objectives Main objective of the course is to introduce new Big Data business intelligence techniques in 4 sectors of Telecom Business (Marketing/Sales, Network Operation, Financial operation and Customer Relation Management). Students will be introduced to following:
  • Introduction to Big Data-what is 4Vs (volume, velocity, variety and veracity) in Big Data- Generation, extraction and management from Telco perspective
  • How Big Data analytic differs from legacy data analytic
  • In-house justification of Big Data -Telco perspective
  • Introduction to Hadoop Ecosystem- familiarity with all Hadoop tools like Hive, Pig, SPARC –when and how they are used to solve Big Data problem
  • How Big Data is extracted to analyze for analytics tool-how Business Analysis’s can reduce their pain points of collection and analysis of data through integrated Hadoop dashboard approach
  • Basic introduction of Insight analytics, visualization analytics and predictive analytics for Telco
  • Customer Churn analytic and Big Data-how Big Data analytic can reduce customer churn and customer dissatisfaction in Telco-case studies
  • Network failure and service failure analytics from Network meta-data and IPDR
  • Financial analysis-fraud, wastage and ROI estimation from sales and operational data
  • Customer acquisition problem-Target marketing, customer segmentation and cross-sale from sales data
  • Introduction and summary of all Big Data analytic products and where they fit into Telco analytic space
  • Conclusion-how to take step-by-step approach to introduce Big Data Business Intelligence in your organization
Target Audience
  • Network operation, Financial Managers, CRM managers and top IT managers in Telco CIO office.
  • Business Analysts in Telco
  • CFO office managers/analysts
  • Operational managers
  • QA managers

Big Data Business Intelligence for Criminal Intelligence Analysis

35小時
技術的進步和越來越多的信息正在改變執法的方式。 Big Data帶來的挑戰幾乎與Big Data的承諾一樣令人生畏。有效存儲數據是這些挑戰之一;有效地分析它是另一回事。 在以講師為主導的現場培訓中，參與者將學習處理Big Data技術的思維方式，評估其對現有流程和政策的影響，並實施這些技術，以識別犯罪活動和預防犯罪。將審查世界各地執法組織的案例研究，以深入了解其採用方法，挑戰和結果。 在培訓結束時，參與者將能夠：
  • 將Big Data技術與傳統的數據收集流程相結合，在調查過程中拼湊出一個故事
  • 實施工業大數據存儲和處理數據分析解決方案
  • 準備一份提案，以採用最適當的工具和程序，使數據驅動的方法能夠進行刑事調查
聽眾
  • 具有技術背景的執法專家
課程形式
  • 部分講座，部分討論，練習和繁重的實踐練習

Pentaho Open Source BI Suite Community Edition (CE)

28小時
Pentaho開源BI套件社區版（CE）是一個商業智能包，提供數據集成，報告，儀表板和加載功能。 在這個有指導意義的現場培訓中，與會者將學習如何最大限度地發揮Pentaho開源BI套件社區版（CE）的功能。 在培訓結束後，參與者將能夠： 安裝並配置Pentaho開源智能套件社區版（CE） 了解Pentaho CE工具及其功能的基本原理使用Pentaho CE構建報告將第三方數據整合到Pentaho CE中在Pentaho CE中使用大數據和分析 聽衆 程序員 BI開發人員 課程的格式 部分講座，部分討論，練習和沈重的練習 注意 要請求本課程的定制培訓，請聯系我們安排。

Business Intelligence with SSAS

14小時
SSAS （ SQL Server Analysis Services）是一種Microsoft SQL Server事務處理（OLAP）和數據挖掘工具，用於分析跨多個數據庫，表或文件的數據。 SSAS提供的語義數據模型由客戶端應用程序（如Power BI ， Excel ，Reporting Services和其他數據可視化工具）使用。 在這個由講師指導的現場培訓（現場或遠程）中，參與者將學習如何使用SSAS分析數據庫和數據倉庫中的大量數據。 在培訓結束時，參與者將能夠：
  • 安裝和配置SSAS
  • 了解SSAS ， SSIS和SSRS之間的關係
  • 應用多維數據建模從數據中提取業務洞察
  • 設計OLAP（在線分析處理）多維數據集
  • 使用MDX（多維查詢和操作多維數據Express離子）查詢語言
  • 使用SSAS部署真實的BI解決方案
聽眾
  • BI（ Business Intelligence ）專業人士
  • 數據分析師
  • Database和數據倉庫專業人員

課程格式
  • 互動講座和討論
  • 大量的練習和練習
  • 在實時實驗室環境中親自實施
課程自定義選項
  • 此培訓基於最新版本的Microsoft SQL Server和SSAS 。
  • 要申請本課程的定制培訓，請聯繫我們安排。

Power BI Dashboards

14小時
了解如何獲取和轉換數據以準備交互式儀表板 Power BI是最受歡迎的Data Visualization工具之一，也是Business Intelligence工具。 Power BI是數據連接器，應用程序和軟件服務的集合，用於從不同來源獲取數據，轉換數據並生成漂亮的報告。 Power BI還允許您為組織發布它們，以便您可以使用移動設備，平板電腦等訪問它們。在此Power BI教程中，我們將向您展示連接多個數據源，數據轉換和創建的分步方法報告如圖表，表格，矩陣，地圖等

IRIS: Document Classification and Data Capture

7小時
IRIS 是企業內容Management （ECM） 系統。借助 IRIS，使用者可以自動進行文檔分類和資料捕獲。 此講師指導的現場培訓（現場或遠端）面向希望使用 IRIS 優化和更新公司內容的內容經理。 培訓結束時，學員將能夠：
  • 使用 IRISXtract 改進業務報告。
  • 使用 IRISPowerscan 自動歸檔文檔。
  • 使用解決方案包處理採購訂單、應付帳款、自動提取電子郵件等。
課程格式
  • 互動講座和討論。
  • 大量的練習和練習。
  • 在即時實驗室環境中實際實現。
課程自訂選項
  • 如需申請本課程的定制培訓，請聯繫我們安排。

Qlik Sense for Data Science

14小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at data analysts and web developers who wish to develop associative models in Qlik Sense. By the end of this training, participants will be able to:
  • Apply Qlik Sense in data science.
  • Use and navigate the Qlik Sense interface.
  • Build a data literate workforce with AI interaction.
  • Create a data-driven enterprise with Qlik Sense.

QlikView Server Administration

14小時
QlikView is a platform that provides organizations self-service business intelligence. QlikView's clean, straightforward, and simple interfaces allow users to easily analyze data and use data discoveries to support decision making. In this instructor-led, live training, participants will learn how to start developing with QlikView. By the end of this training, participants will be able to:
  • Install and configure QlikView
  • Transform data from various sources through QlikView scripting
  • Build data models with QlikView
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.

Qlik: Advanced Topics in Design and Development

14小時
QlikView is a platform that provides organizations self-service business intelligence. QlikView's clean, straightforward, and simple interfaces allow users to easily analyze data and use data discoveries to support decision making. In this instructor-led, live training, participants will learn how to start developing with QlikView. By the end of this training, participants will be able to:
  • Install and configure QlikView
  • Transform data from various sources through QlikView scripting
  • Build data models with QlikView
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.

Data analysis with Tableau

14小時
Tableau可幫助人們查看和理解數據。

Visual Reporting and Analysis with Tableau

14小時
Tableau可幫助人們查看和理解數據。

Tableau Advanced

14小時
Tableau可幫助人們查看和理解數據。

Tableau with Python

14小時
Tableau是一種商業智能和數據可視化工具。 Python是一種廣泛使用的編程語言，它為各種統計和機器學習技術提供支持。 Tableau的數據可視化功能和Python的機器學習功能相結合，可幫助開發人員快速構建適用於各種業務用例的高級數據分析應用程序。 在這個由講師指導的實時培訓中，參與者將學習如何結合使用Tableau和Python來執行高級分析。 Tableau和Python集成將通過TabPy API完成。 在培訓結束時，參與者將能夠：
  • 使用TabPy API集成Tableau和Python
  • 使用Tableau和Python的集成來分析複雜的業務場景，只需幾行Python代碼
聽眾
  • 開發商
  • 數據科學家
課程形式
  • 部分講座，部分討論，練習和繁重的實踐練習

Tableau for Developers

21小時
Tableau是一款商業智能和數據可視化軟件。 Tableau提供了大量開發人員工具和API，用於Tableau功能的集成，自定義，自動化和擴展，以滿足特定於組織的需求。 在這個由講師指導的實時培訓中，參與者將學習如何擴展Tableau的功能以滿足其組織的特定需求。 在培訓結束時，參與者將能夠：
  • 安裝和配置Tableau （桌面，服務器，在線）。
  • 了解使用Tableau進行開發的基礎知識。
  • 使用Tableau創建和發布數據可視化和交互。
  • 使用Tableau的開發人員工具和API來為其組織定制和擴展Tableau的功能。
課程形式
  • 部分講座，部分討論，練習和繁重的實踐練習
注意
  • 要申請本課程的定制培訓，請聯繫我們安排。

Tableau Fundamentals

14小時
這是一個Tableau用戶初學者課程;它適用于任何希望處理數據的人，並且旨在幫助您使用Tableau中的主要功能。 在課程中，您將能夠： 連接到您的數據。 編輯並保存數據源。 了解Tableau術語。 使用Tableau界面/範例有效地創建強大的可視化效果。 創建基本計算，包括基本算術計算，自定義聚合和比率，日期數學和快速表格計算。 使用以下可視化類型來表示您的數據： 交叉標簽地理地圖熱圖樹圖餅圖和條形圖雙軸和組合不同標記類型的圖表突出顯示表散點圖構建儀表板以共享可視化。

Tableau Intermediate Training Course

14小時
Tableau helps people see and understand data.

Data Science with Tableau and R Programming

14小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at data scientists who wish to program in R for Tableau. By the end of this training, participants will be able to:
  • Implement Tableau analytics with R.
  • Return values to Tableau with learning algorithms in R.
  • Structure and visualize R functions in Tableau.
  • Make data driven decisions for business operations.

Tableau Fundamentals to Advanced

28小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at data analysts and data scientists who wish to search, analyze, and visualize data using Tableau. By the end of this training, participants will be able to:
  • Connect to your data.
  • Edit and save a data source.
  • Understand Tableau terminology.
  • Use the Tableau interface / paradigm to effectively create powerful visualizations.
  • Create calculations including arithmetic calculations, custom aggregations and ratios, date math, and table calculations.
  • Represent your data using different visualization types.
  • Build dashboards to share visualizations.

Tableau Server for System Administrators

28小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at system administrators who wish to set up and manage Tableau Server. By the end of this training, participants will be able to:
  • Install and configure Tableau Server.
  • Set up users, roles and permissions to get a team up and running.
  • Access various data sources, manage content and access to the content by users.
  • Automate administrative tasks, including monitoring and log management.
  • Deploying Tableau Server to cluster.

Tableau Prep Builder

21小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at data analysts who wish to prepare and shape data using Tableau Prep Builder. By the end of this training, participants will be able to:
  • Install Tableau Prep.
  • Understand and implement a Data Science Workflow.
  • Read data from a variety of sources, such as Excel and databases.
  • Prepare, shape and sample data for analysis in Tableau Desktop.
  • Explore and validate data.
  • Create and publish Tableau Prep flows.

Data Visualization for Nonprofit using Tableau Public

21小時
This course is designed for the learner who has never used Tableau before, or who may need a refresher.  It will guide you through the steps necessary to create your first visualization from the beginning. You will also learn how to apply essential design principles to your Tableau visualizations. By the end of the course, you will be able to create and share your insights with the broader audience.

Data Visualization Principles for Tableau

14小時
This course teaches you about human perception and how to leverage it to deliver the best insights. You will get familiar with design theory, including Gestalt Laws, pre-attentive attributes, and inclusivity. You will also understand the similarities and differences between exploratory and explanatory analysis. You will discover the usage of the charts and learn how to choose the most suitable one. At the end of the course, you will know how to implement the design principles is visualizations created using Tableau software.

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