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
我真的很喜歡教練的幫助。
Urszula Kuza
課程: Tableau Advanced
Machine Translated
事實上，我們已經為特定問題準備好了解決方案+展示了廣泛的應用程序+通過了知識彙編。 。
Wojciech Michalak
課程: Power BI
Machine Translated
我喜歡練習，因為這是通過重複學習的唯一方法。
David Rushe
課程: Tableau Advanced
Machine Translated
培訓師的知識非常豐富，他可以傳達知識。它涉及參與者互動並解決遇到的問題。
Nina Rokita
課程: Power BI
Machine Translated
培訓師一直與培訓的接受者保持聯繫，根據我們的需求調整步伐，並持續解決我們的問題並回答我們的問題。
Dominika Jaworska
課程: Power BI
Machine Translated
培訓非常一致，我了解了該計劃的許多有趣功能。
Anna Klimczak
課程: Power BI
Machine Translated
做好充分準備，練習練習和老師的知識。
Sandra Przewdzing
課程: Power BI
Machine Translated
與我所遇到的任何培訓機構相比，提供更多關於Power BI的深入範圍。
Mohammed Al Ameer
課程: Power BI
Machine Translated
練習，培訓師提供的其他技巧，可根據要求靈活添加更多見解。
Anna Alechno
課程: Power BI
Machine Translated
我大多喜歡功能BI的可能性。
British American Shared Services Europe
課程: Power BI
Machine Translated
我一般都受益於power bi-web.
Cristina Palii
課程: Power BI
Machine Translated
我真的很喜歡可視化部分。
Alexandra Grigoriu
課程: Power BI
Machine Translated
覆蓋所有Power BI主題，與初學者創建可靠的儀表板和報告相關且有用。
Gabriel Purghel
課程: Power BI
Machine Translated
我喜歡重點和強調自學，玩和閱讀外部資源。沒有申請可以在2天內教授，自學非常重要。
Vlad Andrei Bucur
課程: Power BI
Machine Translated
培訓師樂於回答問題並為我們的實例提供解決方案。
British American Shared Services Europe
課程: Power BI
Machine Translated
我真的從使用DAX和報告中獲益。
Marine Benefits, Inc.
課程: Power BI for Business Analysts
Machine Translated
最後一部分是安全性。
Marine Benefits, Inc.
課程: Power BI for Business Analysts
Machine Translated
我真的很喜歡這個dax。
Chris Amaza - Marine Benefits, Inc.
課程: Power BI for Business Analysts
Machine Translated
我非常喜歡訓練。
Edward Dan Dree Manalad - Marine Benefits, Inc.
課程: Power BI for Business Analysts
Machine Translated
培訓從零開始，讓不熟悉系統的人能夠更高效地在應用程序中導航。我們例子的附加練習也增加了價值。
Rafał Starus - TUiR WARTA S.A
課程: JasperSoft BI
Machine Translated
領導者的方法。好的教學法。
Krzysztof Zimerman - CREDIT SUISSE (Poland) Sp. Z o.o.
課程: Visual Reporting and Analysis with Tableau
Machine Translated
很多關於連接數據庫的新信息.....
CREDIT SUISSE (Poland) Sp. Z o.o.
課程: Visual Reporting and Analysis with Tableau
Machine Translated
老師的能力，沒有任何問題沒有答案。
Wojciech Hudyka - IGT Poland Sp. z o.o.
課程: Tableau for Developers
Machine Translated
學習使用該工具
JOSÉ ALBERTO PABELLO ALAMILLA - Walmart
課程: Tableau Avanzado
Machine Translated
計算的字段和不同的用途
HUMBERTO IBARRA GARCIA - Walmart
課程: Tableau Avanzado
Machine Translated
可以理解的傳遞知識的方式，大量的實踐練習
課程: Power BI
Machine Translated
我喜歡根據我的需求和知識進行調整
Rio TInto
課程: Power BI para Desarrolladores
Machine Translated
對Tableau是以一種可靠的方式“建立起來的”，很明顯教練知道如何最好地向Tableau介紹新手，這使得它看起來非常簡單。
Siemens Gamesa c/o Hemsley Fraser
課程: Tableau Fundamentals
Machine Translated
培訓師走了，找到了他們不知道的問題的答案。
Siemens Gamesa c/o Hemsley Fraser
課程: Tableau Fundamentals
Machine Translated
我真的從主題中受益。
Bristol City Council
課程: Power BI
Machine Translated
培訓師的知識非常好，他們能夠回答有關產品的任何問題。
Bristol City Council
課程: Power BI
Machine Translated
我主要是從了解甘特圖表中獲益。
Sarah Drummond - Siemens Gamesa c/o Hemsley Fraser
課程: Tableau Advanced
Machine Translated
培訓師很精緻，他能夠利用他對課程的豐富知識來使用我們的數據，儘管我們的工作背景為0。
Mc Gyver Pascua - Sykes Asia, Inc.
課程: Power BI
Machine Translated
我很喜歡學習Power BI的經驗。
Sykes Asia, Inc.
課程: Power BI
Machine Translated
佈局前準備原始數據。
Ayie Delos Santos - Sykes Asia, Inc.
課程: Power BI
Machine Translated
我最喜歡DAX功能主題以及培訓師對解決不合適輸出的渴望，他根據受眾的理解程度說話。
Anabelle Anore - Sykes Asia, Inc.
課程: Power BI
Machine Translated
我很喜歡喬納森提供的講座的實際應用......
Sykes Asia, Inc.
課程: Power BI
Machine Translated
該工具非常有趣。
Pernod Ricard Hong Kong Limited
課程: Power BI for Business Analysts
Machine Translated
非常實用，使用我們的內部數據來練習。
Pernod Ricard Hong Kong Limited
課程: Power BI for Business Analysts
Machine Translated
清晰，有條理地組織培訓主題。適合那些從未使用過PowerBI能夠創建合理的儀表板和報告的人。
Pernod Ricard Hong Kong Limited
課程: Power BI for Business Analysts
Machine Translated
交流自由和培訓師的開放性，基於真實案例/數據的練習。另外，我喜歡這樣一個事實：如果有人問了一個問題，那麼教練會回答所有問題。 Go協調讚美也是一種回歸到第二天的問題之一，呈現出不同的選項來解決這個問題/。
Artur Niestój - HSBC Service Delivery (Polska) Sp. z o.o.
課程: Data analysis with Tableau
Machine Translated
可視化領域的實踐練習。
Magdalena Piorunek - HSBC Service Delivery (Polska) Sp. z o.o.
課程: Data analysis with Tableau
Machine Translated
當受訓者要求時，我受益於切換主題的良好解釋和能力。
McArthurGlen
課程: Power BI
Machine Translated
我最喜歡非常活潑和輕鬆..
Rey Jasper Matias - Sykes Asia, Inc.
課程: Power BI
Machine Translated
培訓師盡可能地聽取了他的聽眾的需求，我們能夠根據我們的需求進行培訓，科斯塔斯專門針對高級培訓的基本培訓問題準備了材料，付出了很多努力和工作而且很感激。
Chloe Horton - Siemens Gamesa c/o Hemsley Fraser
課程: Tableau Advanced
Machine Translated
培訓是根據我們的要求量身定制的，這是我們在開始之前介紹的。此外，培訓師提出或製定了持續選擇的問題，作為我們的額外或更有趣的問題。
BNY Mellon (Poland) Sp. z o. o.
課程: JasperReports
Machine Translated
在產品知識方面, 他確實很有知識, 非常願意回答問題。
Cherry Espinili - Infinit-O Manila
課程: Tableau Fundamentals
Machine Translated
我主要是受益于練習和樣本案例。
Ann Olano - Infinit-O Manila
課程: Tableau Fundamentals
Machine Translated
培訓根據我們的需要和知識調整培訓。他理解參與者使用 Power BI 的經驗。
Cristian Tudor - Gilbarco ACIS SRL
課程: Creating Dashboards Using Microsoft Power BI
Machine Translated
學習新產品是令人興奮的, 雖然它與 MS Excel 有相似之處, 但它在許多方面當然是不同的
Recep Köroglu - European Patent Office
課程: Tableau Fundamentals
Machine Translated
可以理解的傳遞知識的方式，大量的實踐練習
課程: Power BI
Machine Translated
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
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.
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.
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.
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.
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。
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。
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
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.
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.
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
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
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
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
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。
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。
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。
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
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
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。
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。
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.
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.
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.
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.
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.
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.
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
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
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。
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。
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。
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.
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.
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.
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.
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.
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.
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.
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.
21小時
Pentaho數據集成是一個開源數據集成工具，用于定義作業和數據轉換。 在這種有指導性的現場培訓中，與會者將學習如何使用Pentaho Data Integration強大的ETL功能和豐富的GUI來管理整個大數據生命周期，從而最大限度地提高組織的數據價值。 在培訓結束後，參與者將能夠： 創建，預覽和運行包含步驟和跳躍的基本數據轉換配置和保護Pentaho Enterprise Repository 利用不同來源的數據，並以分析已准備好的格式生成單一統一版本的真相。 向第三方應用程序提供結果以供進一步處理 聽衆 數據分析師 ETL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
14小時
Dashbuilder是一個開源Web應用程序，用於可視化地創建業務儀表板和報告。
在這個由講師指導的實時培訓中，參與者將學習如何使用Dashbuilder創建業務儀表板和報告。
在培訓結束時，參與者將能夠：
- 使用拖放操作可視化配置和個性化儀表板
- 使用圖表庫創建不同類型的可視化
- 定義交互式報告表
- 創建和編輯內聯KPI（關鍵績效指標）
- 自定義公制顯示器的外觀
聽眾
- 經理
- 分析師
課程形式
- 部分講座，部分討論，練習和繁重的實踐練習
在這個由講師指導的實時培訓中，參與者將學習如何使用Dashbuilder創建業務儀表板和報告。
在培訓結束時，參與者將能夠：
- 使用拖放操作可視化配置和個性化儀表板
- 使用圖表庫創建不同類型的可視化
- 定義交互式報告表
- 創建和編輯內聯KPI（關鍵績效指標）
- 自定義公制顯示器的外觀
聽眾
- 經理
- 分析師
課程形式
- 部分講座，部分討論，練習和繁重的實踐練習
7小時
Dashbuilder是一個開源Web應用程序，用於可視化地創建業務儀表板和報告。
在這個由講師指導的實時培訓中，參與者將學習如何設置，配置，集成和部署Dashbuilder 。
在培訓結束時，參與者將能夠：
- 從異構源（如JDBC數據庫和文本文件）中提取數據
- 使用連接器連接到第三方系統和平台，例如j BPM
- 為用戶配置角色，權限和訪問控制
- 將Dashbuilder部署到實時生產環境
聽眾
- 開發商
- IT和系統架構師
課程形式
- 部分講座，部分討論，練習和繁重的實踐練習
在這個由講師指導的實時培訓中，參與者將學習如何設置，配置，集成和部署Dashbuilder 。
在培訓結束時，參與者將能夠：
- 從異構源（如JDBC數據庫和文本文件）中提取數據
- 使用連接器連接到第三方系統和平台，例如j BPM
- 為用戶配置角色，權限和訪問控制
- 將Dashbuilder部署到實時生產環境
聽眾
- 開發商
- IT和系統架構師
課程形式
- 部分講座，部分討論，練習和繁重的實踐練習
21小時
In this instructor-led, live training in 台灣 (onsite or remote), participants will learn how to use Microsoft Power BI to analyze and visualize data using a series of sample data sets.
By the end of this training, participants will be able to:
- Create visually compelling dashboards that provide valuable insights into data.
- Obtain and integrate data from multiple data sources.
- Build and share visualizations with team members.
- Adjust data with Power BI Desktop.
By the end of this training, participants will be able to:
- Create visually compelling dashboards that provide valuable insights into data.
- Obtain and integrate data from multiple data sources.
- Build and share visualizations with team members.
- Adjust data with Power BI Desktop.
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