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所在平台: Udemy |
课程主页: https://www.udemy.com/course/business-intelligence-and-data-analytics/
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课程名称：数据分析与商业智能 概述：欢迎参加由Uplatz提供的数据分析与商业智能课程。本课程深入探讨数据分析和商业智能的概念及其应用，帮助学员熟悉商业分析领域的工具与技术，并掌握将它们应用于实际商业场景的技能。如果您希望在数据分析和商业智能这一热门领域开启成功的职业生涯，并获得丰厚的薪酬，这门课程将非常适合您。 本课程不仅详细介绍了理解数据并进行有意义分析的内容，还简要介绍了机器学习和数据科学的概念。商业智能系统将数据收集、存储和知识管理与数据分析结合，旨在评估和转化复杂数据为有意义的、可操作的信息，支持更有效的战略、战术和运营决策。 组织的商业智能环境由多种技术、应用、流程和策略组成，用于收集、分析、展示和传播内部及外部业务数据。商业智能与分析包括数据挖掘、预测分析和统计分析等方法，以分析和转化数据为有用的信息，识别和预测趋势与结果，最终做出更智能的数据驱动业务决策。 现代商业智能解决方案支持自助分析，使最终用户能够轻松生成自己的报告。用户可以通过简单的用户界面与灵活的商业智能后端软件，连接到包括NoSQL数据库、Hadoop系统、云平台和传统数据仓库等多种数据源，形成统一的异构数据视图。 本课程旨在培养一批跨领域的专业人才，具备商业流程分析、技术管理的素养，掌握数据科学的各个方面，如预测建模、分析报告、GIS映射、细分分析和数据可视化，并了解机器学习和深度学习的基本概念。学员将获得整合前沿信息与分析技术的能力，以及最佳实践与应用商业方法。 数据分析与商业智能课程结合了分析和专业技能，帮助您成为一种质疑假设并基于事实做出证据驱动选择的管理者。您将学习新技能，以提高产品、服务和策略，带领企业在技术不断发展的市场中前行。课程涵盖机器学习、语言处理、数据挖掘、数据建模（包括预测建模）、优化、NoSQL和自然语言处理等主题，涉及数据革命的前沿知识。 课程大纲包括： - 商业智能概念、案例及应用入门 - 预测建模入门 - NoSQL入门 - 层次聚类 - Salesforce入门 - 自然语言处理入门 - Apache服务器入门 - 商业智能深入探讨 - 数据仓库 - 数据类型 - 移动商业智能 - 实时商业智能 - 数据分析 - 数据分析与商业分析的区别 - 嵌入式分析 - 生存分析 - 机器学习技术 - 地理空间预测分析 - 队列分析 - 数据挖掘 - 异常检测 - 统计相关性 - 聚类分析 - DB Scan - 回归模型 - 基于提取的摘要 - 机器学习在商业智能中的应用 - 机器学习与商业智能的关系 - 机器学习如何改善商业智能 - 理解数据仓库 - 理解数据集市 - 理解数据维度 - 理解数据保管建模 - 理解链接和卫星等内容。 通过本课程，学员将为在数据分析与商业智能的职业生涯打下坚实基础。
A warm welcome to the Data Analytics & Business Intelligence course by Uplatz.Uplatz brings this detailed course on Data Analytics & Business Intelligence to help you get familiar with the concepts and application of business analysis, the tools & technologies involved in business analytics domain, and finally to get you skilled in applying the same to practical business scenarios.If you wish to make a successful career in this super trending area of data analytics and business intelligence commanding huge pay packages, then this is perfectly the right course for you to get you started. Besides going into detail of understanding data and performing meaningful analytics on it, this Business Intelligence & Data Analytics course also introduces you briefly to the concepts of machine learning and data science.Data gathering, storage, and knowledge management are combined with data analysis in business intelligence systems to evaluate and transform complex data into meaningful, actionable information that can be used to support more effective strategic, tactical, and operational insights and decision-making. An organization's business intelligence environments are made up of a number of technologies, applications, processes, strategies, products, and technological architectures that are used to gather, analyze, display, and disseminate internal and external business data.The use of methodologies such as data mining, predictive analytics, and statistical analysis in order to analyze and transform data into useful information, identify and anticipate trends and outcomes, and ultimately make smarter, data-driven business decisions, is referred to as business intelligence and analytics, a data management solution and business intelligence subset.A business intelligence platform allows companies to take use of their current data architecture and construct unique business intelligence apps that allow analysts to query and view data. Self-service analytics is supported by modern business intelligence solutions, making it simple for end users to build their own reports. Users may connect to a variety of data sources, including NoSQL databases, Hadoop systems, cloud platforms, and traditional data warehouses, using simple user interfaces mixed with flexible business intelligence backend software to produce a unified picture of their heterogeneous data.This Business Intelligence and Data Analytics course aims to produce a select group of skilled individuals who are cross-trained in business process analysis, technology management, and technically skilled in all aspects of data science, such as predictive modelling, analytical reporting, GIS mapping, segmentation analysis, and data visualization along with machine learning & deep learning. Students will acquire the skills to integrate cutting edge information and analytics technologies with best practices and applied business methods.The Business Intelligence & Analytics course combines analytical and professional skills to help you become the type of manager who questions assumptions and makes evidence-based choices based on facts. You'll learn new skills that will help you improve your goods, services, and strategies while leading your firm through markets that are always changing due to technological advancements. Machine learning, language processing, data mining, data modeling including predictive modeling, optimization, NoSQL, NLP are among the topics covered in the curriculum, which are at the forefront of the data revolution. Classes go beyond the fundamentals of understanding data and using it for making business decisions, to addressing essential business ideas.Data Analytics & Business Intelligence - course curriculumIntroduction to BI Concepts, Examples, and ApplicationsIntroduction to Predictive ModelingIntroduction to NoSQLHierarchical ClusteringIntroduction to SalesforceIntroduction to NLPIntroduction to Apache ServerBusiness Intelligence deep-diveData WarehousingTypes of DataMobile BIReal-time BIData AnalyticsData Analytics vs. Business AnalysisEmbedded AnalyticsCollection AnalyticsSurvival AnalyticsMachine Learning TechniquesGeospatial Predictive AnalyticsCohort AnalysisData MiningAnomaly DetectionStatistically Sound AssociationsCluster AnalysisDB ScanRegression ModelsExtraction-based SummarizationMachine Learning in BIMachine Learning vs. BIHow ML can make BI betterUnderstanding Data WarehousingUnderstanding Data MartUnderstanding Data DimensionsUnderstanding Data Vault ModelingUnderstanding Links and Satellites
