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    • Big Data Analytics

    필터링 기준

    "big data analytics"에 대한 390개의 결과

    • University of Colorado Boulder

      University of Colorado Boulder

      Developing Industrial Internet of Things

      획득할 기술: Accounting, Big Data, Computer Architecture, Computer Graphics, Computer Networking, Computer Security Models, Data Management, Design and Product, Hardware Design, Human Computer Interaction, Interactive Design, Machine Learning, Market Analysis, Marketing, Mathematical Theory & Analysis, Mathematics, Network Architecture, Operating Systems, Security Engineering, Strategy and Operations, System Security

      4.6

      (548개의 검토)

      Intermediate · Specialization

    • The State University of New York

      The State University of New York

      Big Data, Genes, and Medicine

      획득할 기술: Bioinformatics, Data Analysis, Probability & Statistics, Basic Descriptive Statistics

      4.2

      (243개의 검토)

      Advanced · Course

    • University of Illinois at Urbana-Champaign

      University of Illinois at Urbana-Champaign

      Introduction to Accounting Data Analytics and Visualization

      획득할 기술: Data Visualization Software, Machine Learning, Financial Accounting, Strategy and Operations, Correlation And Dependence, Theoretical Computer Science, Regression, Data Visualization, Microsoft Excel, Financial Analysis, Plot (Graphics), Critical Thinking, Data Management, Probability & Statistics, Research and Design, Data Analysis, Tableau Software, Software, Accounting, Data Analysis Software, Analytics, Statistical Analysis, Taxes, Pivot Table, Business Analysis, Analysis, General Statistics, Data Structures, Management Accounting, Spreadsheet Software

      4.8

      (381개의 검토)

      Beginner · Course

    • Databricks

      Databricks

      Apache Spark (TM) SQL for Data Analysts

      획득할 기술: Data Analysis, SQL, Probability & Statistics, Statistical Programming, Exploratory Data Analysis, Big Data, Business Analysis, Apache, Statistical Analysis, Databases, Data Management

      4.5

      (344개의 검토)

      Intermediate · Course

    • University of Illinois at Urbana-Champaign

      University of Illinois at Urbana-Champaign

      Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud

      획득할 기술: Big Data, Data Architecture, Network Architecture, Graphs, Theoretical Computer Science, Machine Learning, Computer Programming, Software Architecture, Computer Architecture, Apache, Computer Networking, Deep Learning, Data Management, Software Engineering, Computational Thinking, Databases, Distributed Computing Architecture, Database Theory

      4.3

      (322개의 검토)

      Mixed · Course

    • LearnQuest

      LearnQuest

      Data Processing with Azure

      획득할 기술: SQL, Python Programming, Data Management, Cloud Storage, General Statistics, Computer Programming, Probability & Statistics, Cloud Computing, Extract, Extract, Transform, Load, Statistical Programming

      3.7

      (64개의 검토)

      Intermediate · Course

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      Microsoft

      Microsoft

      Explore Core Data Concepts in Microsoft Azure

      획득할 기술: Data Analysis, SQL, Data Visualization Software, Data Visualization, Extract, Transform, Load, Databases, Data Management, NoSQL, Analytics, Cloud Computing, Database Administration, Statistical Programming, Analysis, Business Analysis, Microsoft Azure

      4.7

      (159개의 검토)

      Beginner · Course

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      University of California San Diego

      University of California San Diego

      Graph Analytics for Big Data

      획득할 기술: Mathematics, Big Data, Graphs, NoSQL, Data Management, Analytics, Graph Theory, Databases

      4.3

      (1.2k개의 검토)

      Mixed · Course

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      IBM

      IBM

      IBM Data Analyst

      획득할 기술: Algebra, Apache, Big Data, Business Analysis, Computational Logic, Computer Programming, Computer Programming Tools, Correlation And Dependence, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Structures, Data Visualization, Data Visualization Software, Data Warehousing, Database Administration, Database Application, Databases, Econometrics, Exploratory Data Analysis, Extract, Transform, Load, General Statistics, Geovisualization, Leadership and Management, Linear Regression, Machine Learning, Mathematical Theory & Analysis, Mathematics, Microsoft Excel, NoSQL, Operating Systems, Plot (Graphics), Probability & Statistics, Professional Development, Python Programming, Regression, Regression Analysis, SQL, Spreadsheet Software, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Statistical Visualization, System Programming, Theoretical Computer Science

      4.6

      (50.6k개의 검토)

      Beginner · Professional Certificate

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      PwC

      PwC

      Data-driven Decision Making

      획득할 기술: Decision Making, Data Visualization Software, Big Data, Data Visualization, Entrepreneurship, Leadership and Management, Data Management, Analytics, Data Analysis, Data Type, Analysis, Business Analysis, Data Analysis Software

      4.6

      (5.7k개의 검토)

      Beginner · Course

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      Pontificia Universidad Católica de Chile

      Pontificia Universidad Católica de Chile

      Certificado en Toma de Decisiones Basadas en Datos

      학점 제공

      Mastertrack

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      Pontificia Universidad Católica de Chile

      Pontificia Universidad Católica de Chile

      Magíster en Analítica para los Negocios

      학위 취득

      Degree

    big data analytics과(와) 관련된 검색

    大數據分析:商業應用與策略管理 (big data analytics: business applications and strategic decisions)
    graph analytics for big data
    big data analytical platform on alibaba cloud
    big data analysis with scala and spark
    big data analysis with scala and spark (scala 2 version)
    big data analysis deep dive
    big data analysis to a slide presentation
    modern big data analysis with sql
    1234…33

    요약하자면, 여기에 가장 인기 있는 big data analytics 강좌 10개가 있습니다.

    • Developing Industrial Internet of Things: University of Colorado Boulder
    • Big Data, Genes, and Medicine: The State University of New York
    • Introduction to Accounting Data Analytics and Visualization: University of Illinois at Urbana-Champaign
    • Apache Spark (TM) SQL for Data Analysts: Databricks
    • Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud: University of Illinois at Urbana-Champaign
    • Data Processing with Azure: LearnQuest
    • Explore Core Data Concepts in Microsoft Azure: Microsoft
    • Graph Analytics for Big Data: University of California San Diego
    • IBM Data Analyst: IBM
    • Data-driven Decision Making: PwC

    Machine Learning에서 학습할 수 있는 스킬

    Python 프로그래밍 (33)
    TensorFlow (32)
    심층 학습 (30)
    인공 신경 회로망 (24)
    빅 데이터 (18)
    통계 분류 (17)
    강화 학습 (13)
    대수학 (10)
    베이지안 (10)
    선형 대수 (10)
    선형 회귀 (9)
    Numpy (9)

    Big Data Analytics에 대한 자주 묻는 질문

    • Big data analytics refers to the application of advanced data analysis techniques to datasets that are very large, diverse (including structured and unstructured data), and often arriving in real time. The ability to process data at this scale is increasingly essential to navigating today’s business world, and it is at the core of important applications such as machine learning, business intelligence, financial engineering, and other software tools to enable data-informed decision-making.

      Computer programs have been used to assist with data analysis for decades, but tools like Microsoft Excel and traditional relational database management systems (RDBMS) queried with SQL are not capable of handling today’s high-volume, high-velocity datasets. Instead, today’s data management professionals rely on high-powered data infrastructure designed to work with distributed file systems and cloud computing resources - particularly the open-source Apache Hadoop ecosystem, including high-speed data processing with Apache Spark and distributed SQL engines like Apache Hive.‎

    • Organizations of all types and sizes are seeking ways to leverage the possibilities of big data to improve operations through reduced costs and faster decision-making, create new products and services, or advance our knowledge about the world. Big data analytics skills can thus open up a wide range of career opportunities, from working as a “quant” on Wall Street to developing navigation systems for autonomous vehicles to helping to discover more effective medicines and drugs in health science.

      Two of the most broadly-applicable roles in this field are data engineers, who build the data infrastructure needed to deliver big data-scale datasets efficiently and reliably, and the data scientists responsible for analyzing them. These roles are in high demand, and are highly-paid as well; according to Glassdoor, data engineers earn an average annual salary of $102,864, and data scientists earn an average annual salary of $113,309.‎

    • Absolutely! Data science is one of the most popular topics to learn about on Coursera, and there are a variety of options to build your skills in big data analytics. You can take online courses and Specializations from top-ranked schools like the University of Pennsylvania and the University of California San Diego, as well as leading companies like IBM, PwC, Cloudera, and Google Cloud. And regardless of where you choose to learn from, Coursera gives you the ability to access course materials and complete assignments on a flexible schedule, making this a great fit for students and mid-career professionals alike.‎

    • Before you start learning big data analytics, it’s helpful to have an understanding of database management and the fundamentals of how programming languages work. Specifically, experience with SQL, Python, Java, or R can be useful when studying big data analytics. You also may find it beneficial to know how to work with Hadoop and Linux and use basic math and statistics. Additionally, strong analytical skills and a curiosity about playing with data come in handy when you learn big data analytics.‎

    • The right people for roles in big data analytics are inquisitive problem solvers who like working with numbers and using statistics to sort through large amounts of data. They typically have work experience or coursework in high-level math or computer programming. A background in behavioral analysis can also be useful for roles in big data analytics because individuals often seek to understand or predict what influences the behavior represented by data. Big data analysts may often need soft skills, such as communication and collaboration skills they use when explaining what they see in the data and working with team members on projects.‎

    • If you like working with numbers and are comfortable using statistical techniques, learning big data analytics may be right for you. The amount of data collected on a daily basis is already massive and continues to grow, so organizations need analysts who can curate and prepare data for businesses, governments, and other groups to use. Learning big data analytics may interest you if you possess strong analytical and problem-solving skills and want to apply those skills to sorting and analyzing data to find what’s useful for a client. You may be able to use the knowledge you gain to land an internship or seek a career in data science filling roles in a variety of industries.‎

    이 FAQ 콘텐츠는 정보 전달 목적만으로 사용할 수 있습니다. 학습자는 과정 및 기타 학점 정보가 개인적, 직업적 및 재정적 목표에 부합하는지 확인하기 위해 추가 조사를 수행하는 것이 좋습니다.
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