Expert Certificate: Marketing Data Analysis & Data Analytics
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Welcome to Program: Expert Certificate: Marketing Data Analysis & Data Analytics by MTF Institute
Course provided by MTF Institute of Management, Technology and Finance
MTF is the global educational and research institute with HQ at Lisbon, Portugal, focused on business & professional hybrid (on-campus and online) education at areas: Business & Administration, Science & Technology, Banking & Finance.
MTF R&D center focused on research activities at areas: Artificial Intelligence, Machine Learning, Data Science, Big Data, WEB3, Blockchain, Cryptocurrency & Digital Assets, Metaverses, Digital Transformation, Fintech, Electronic Commerce, Internet of Things.
MTF is the official partner of: IBM, Intel, Microsoft, member of the Portuguese Chamber of Commerce and Industry.
MTF is present in 215 countries and has been chosen by more than 701 000 students.
Course Author:
Dr. Alex Amoroso is a seasoned professional with a rich background in academia and industry, specializing in research methodologies, strategy formulation, and product development. With a Doctorate Degree from the School of Social Sciences and Politics in Lisbon, Portugal, where she was awarded distinction and honour for her exemplary research, Alex Amoroso brings a wealth of knowledge and expertise to the table.
In addition to her doctoral studies, Ms. Amoroso has served as an invited teacher, delivering courses on to wide range of students from undergraduate level to business students of professional and executives courses. Currently, at EIMT in Zurich, Switzerland, she lectures for doctoral students, offering advanced instruction in research design and methodologies, and in MTF Institute Ms. Amoroso is leading Product Development academical domain.
In synergy between academical and business experience, Ms. Amoroso achieved high results in business career, leading R&D activities, product development, strategic development, market analysis activities in wide range of companies. She implemented the best market practices in industries from Banking and Finance, to PropTech, Consulting and Research, and Innovative Startups.
Alex Amoroso’s extensive scientific production includes numerous published articles in reputable journals, as well as oral presentations and posters at international conferences. Her research findings have been presented at esteemed institutions such as the School of Political and Social Sciences and the Stressed Out Conference at UCL, among others.
With a passion for interdisciplinary collaboration and a commitment to driving positive change, Alex Amoroso is dedicated to empowering learners and professionals for usage of cutting edge methodologies for achieving of excellence in global business world.
Data analysis is the process of collecting, cleaning, and organizing data to uncover patterns, insights, and trends that can help individuals and organizations make informed decisions. It involves examining raw data to find answers to specific questions, identify potential problems, or discover opportunities for improvement.
Data analysts transform raw data into actionable insights to help organisations improve operations, strategies, and customer experiences. Core skills include statistical analysis, critical thinking, data visualisation, and proficiency in tools like Excel, SQL, Python, and Tableau.
Learning data analysis skills is crucial for career building in today’s data-driven world, both for professional positions and managers of all levels.
Marketing Data Analysis and Data Analytics are closely related, but with a specific focus. Here’s a breakdown:
Marketing Data Analysis:
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Focus: Analyzing data specifically related to marketing efforts. This includes data from campaigns, customer interactions, website traffic, social media, and more.
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Goal: To understand the effectiveness of marketing strategies, identify trends, and gain insights into customer behavior to optimize campaigns and improve ROI.
Data Analytics:
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Focus: A broader field that involves collecting, organizing, and analyzing data from various sources to extract meaningful insights and make informed decisions.
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Goal: To identify patterns, trends, and correlations in data to solve business problems, improve processes, and gain a competitive advantage.
Importance for Companies:
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Enhanced Customer Understanding: Data analytics provides deep insights into customer behavior, preferences, and needs, allowing companies to personalize marketing efforts and build stronger customer relationships.
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Improved Campaign Effectiveness: By analyzing campaign data, companies can identify what’s working and what’s not, optimize campaigns in real-time, and maximize ROI.
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Data-Driven Decision Making: Data analytics empowers companies to make informed decisions based on evidence rather than intuition, leading to better outcomes.
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Competitive Advantage: Companies that effectively leverage data analytics gain a competitive edge by understanding their market better, identifying new opportunities, and adapting quickly to changing conditions.
Importance for Career Building:
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High Demand: Data analytics skills are in high demand across industries, including marketing. Developing these skills can open up a wide range of career opportunities.
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Valuable Skills: Data analysis and interpretation are crucial skills for marketing professionals. They enable you to demonstrate the impact of your work, make data-driven recommendations, and contribute to strategic decision-making.
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Career Advancement: Proficiency in data analytics can accelerate career progression and lead to leadership roles.
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Increased Earning Potential: Professionals with data analytics skills often command higher salaries due to the value they bring to organizations.
Marketing Data Analysis and Data Analytics are essential for both companies and individuals in today’s data-driven world. Companies that leverage these skills gain a competitive advantage, while individuals who develop these skills enhance their career prospects and earning potential.
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3PresentationVideo lesson
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4Module Slide-deckText lesson
Please, look to attached files
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5IntroductionVideo lesson
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6Data Collection and AcquisitionVideo lesson
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7Data Cleaning and PreparationVideo lesson
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8Exploratory Data Analysis (EDA)Video lesson
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9Statistical AnalysisVideo lesson
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10Data VisualisationVideo lesson
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11Predictive AnalyticsVideo lesson
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12Data Interpretation and ReportingVideo lesson
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13Data Privacy and EthicsVideo lesson
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14Tools and Software for Data AnalysisVideo lesson
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15Building a Data Analyst PortfolioVideo lesson
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16Career Development and Job Market TrendsVideo lesson
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17Practical exercisesVideo lesson
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18Next StepsVideo lesson
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19Module presentationVideo lesson
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20Module overviewVideo lesson
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21ExcelVideo lesson
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22Excel Practical TaskText lesson
please, download attachments for practicing
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23SQLVideo lesson
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24Exercise: Retrieve and Analyze Customer and Order Data with SQLiteText lesson
please, download attachments for practing
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25PythonVideo lesson
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26Handling Missing Data and Analysing the Data with PythonText lesson
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27R practiceVideo lesson
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28Exercise: Conduct Statistical Analysis Using RText lesson
please, download attachments for practicing
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29TableauVideo lesson
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30Exercise: Visualizing Global Earthquake Data with Geographic RepresentationText lesson
please, download attachments for practicing
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31Next stepsVideo lesson
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32Introduction to Data-Based Decision Making (DBDM)Text lesson
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33The Data Landscape: Types, Sources, and Quality.Text lesson
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34Data Collection and PreparationText lesson
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35Descriptive Analytics: Understanding the "What"Text lesson
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36Diagnostic Analytics: Exploring the "Why"Text lesson
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37Predictive Analytics: Forecasting the "Future"Text lesson
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38Prescriptive Analytics: Recommending the "How"Text lesson
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39Data-Driven Culture and Organizational ChangeText lesson
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40Tools and Technologies for Data-Based Decision MakingText lesson
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41Case Studies in Data-Based Decision MakingText lesson
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42Module PresentationVideo lesson
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43Module Slide-deck and materialsText lesson
Please, look to attached files
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44Module OverviewVideo lesson
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45Types of Marketing DataVideo lesson
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46M1_A01_The Role of Data Analysis in Modern MarketingText lesson
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47M1_A02_Data Sources for Marketers_ Internal and External OptionsText lesson
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48Developing an Analytical MindsetVideo lesson
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49M2_A03_Key Marketing MetricsText lesson
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50M2_A04_Limitations and Challenges in Metrics-Based Decision-MakingText lesson
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51Data Analysis Frameworks in MarketingVideo lesson
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52M3_A05_Understanding Statistical Concepts for MarketersText lesson
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53M3_A06_Key Analytical ModelsText lesson
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54M4_A07_Principles of Data-Driven SegmentationText lesson
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55M4_A08_Theories of Customer SegmentationText lesson
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56M4_A09_Linking Segmentation to Campaign StrategiesText lesson
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57Predictive Analytics A Marketer’s PerspectiveVideo lesson
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58M5_A10_Applications in MarketingText lesson
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59M5_A11_Introduction to Forecasting TechniquesText lesson
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60Designing Effective AB TestsVideo lesson
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61M6_A12_Theoretical Basis of Campaign AnalysisText lesson
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62M6_A13_Continuous Optimisation FrameworksText lesson
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63M7_A14_Ethical Considerations in Marketing DataText lesson
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64M7_A15_Bias in Marketing DataText lesson
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65M7_A16_Sustainability in Marketing Data PracticesText lesson
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66M8_A17_The Data-Driven Marketing CycleText lesson
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67M8_A18_Building a Data-Informed Marketing CultureText lesson
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68Short SummaryText lesson
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69Study Guide and QuizText lesson
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70Briefing Document: Data Analysis in Modern MarketingText lesson

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