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.
This instructor-led, live training in 台灣 (online or onsite) is aimed at intermediate to advanced-level data architects who wish to learn skills for installing, configuring, managing, and maintaining a Tableau server.
By the end of this training, participants will be able to:
Have an in-depth understanding of the Tableau Server architecture.
Understand Tableau Server processes and functions.
User Tableau Server to automate tasks.
Configure and manage the Tableau Server.
Set up Tableau Server for high availability and scalability.
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.
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.
This instructor-led, live training in 台灣 (online or onsite) is aimed at beginner to intermediate-level business analysts, data analysts, and developers who wish to learn the fundamentals of DAX in Power BI.
By the end of this training, participants will be able to:
Have a comprehensive understanding of Data Analysis Expressions (DAX) in Power BI.
Create custom calculations and expressions in Power BI for analyzing data and deriving insights.
This instructor-led, live training in 台灣 (online or onsite) is aimed at beginner to advanced-level MicroStrategy architects who wish to develop schemas, change management, and use modeling tools to manage the development cycle of MicroStrategy apps.
By the end of this training, participants will be able to:
Fully understand the concepts and architecture of data warehousing.
Understand how to use analytics, desktop objects, and schemas.
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
商業智能,培訓,課程,培訓課程, 企業商業智能培訓, 短期商業智能培訓, 商業智能課程, 商業智能周末培訓, 商業智能晚上培訓, 商業智能訓練, 學習商業智能, 商業智能老師, 學商業智能班, 商業智能遠程教育, 一對一商業智能課程, 小組商業智能課程, 商業智能培訓師, 商業智能輔導班, 商業智能教程, 商業智能私教, 商業智能輔導, 商業智能講師Business Intelligence,培訓,課程,培訓課程, 企業Business Intelligence培訓, 短期Business Intelligence培訓, Business Intelligence課程, Business Intelligence周末培訓, Business Intelligence晚上培訓, Business Intelligence訓練, 學習Business Intelligence, Business Intelligence老師, 學Business Intelligence班, Business Intelligence遠程教育, 一對一Business Intelligence課程, 小組Business Intelligence課程, Business Intelligence培訓師, Business Intelligence輔導班, Business Intelligence教程, Business Intelligence私教, Business Intelligence輔導, Business Intelligence講師
Course Discounts
No course discounts for now.
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As a Business Development Manager you will:
expand business in Taiwan
recruit local talent (sales, agents, trainers, consultants)
recruit local trainers and consultants
We offer:
Artificial Intelligence and Big Data systems to support your local operation
high-tech automation
continuously upgraded course catalogue and content
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If you are interested in running a high-tech, high-quality training and consulting business.