536 Data Analyst courses delivered Online

In today's data-driven world, the demand for skilled analysts is rising. Our Intelligence Analyst Certification course provides the knowledge and expertise to succeed in this critical field. With eight modules covering essential topics, this Intelligence Analyst course equips you with the theoretical foundations needed to excel as an intelligence analyst. Statistics reveal an increasing demand for skilled intelligence analysts in both the public and private sectors. In a complex world, gathering, analysing, and interpreting information is crucial for informed decision-making and safeguarding national security. Enrolling in our Intelligence Analyst Certification course positions you for a rewarding and impactful career in this Intelligence Analyst field. Learning Outcomes: By completing this Intelligence Analyst course, you will be able to: Define the role and principles of intelligence analysis, including its purpose, scope, and ethics, with our Intelligence Analyst course Understand its historical context and importance in modern security settings with our Intelligence Analyst course Use the intelligence cycle to effectively gather, evaluate, analyse, and share intelligence with our Intelligence Analyst course Apply critical thinking and structured techniques to interpret complex information accurately through our Intelligence Analyst course Follow best practices in intelligence analysis, including data collection, source evaluation, and report synthesis. Consider legal and ethical aspects such as privacy, data protection, and responsible intelligence use. "Intelligence Analyst Certification" Our comprehensive Intelligence Analyst Certification course covers eight modules essential for success in this field. You'll learn to define intelligence analysis and understand its development and the intelligence cycle. Gain critical thinking skills, and master the analysis process and best practices. Explore intelligence's role in national security, legal issues, and ethics. Finally, discover your responsibilities and functions as an analyst. Start your journey towards becoming a skilled intelligence analyst today. CPD 10 CPD hours / points Accredited by CPD Quality Standards Module 01: Defining Intelligence Analysis 17:29 1: Defining Intelligence Analysis Preview 17:29 Module 02: Development of Intelligence Analysis 18:04 2: Development of Intelligence Analysis 18:04 Module 03: The Intelligence Cycle 12:19 3: The Intelligence Cycle 12:19 Module 04: Critical Thinking and Structuring 17:12 4: Critical Thinking and Structuring 17:12 Module 05: Analysis Process and Best Practice 25:15 5: Analysis Process and Best Practice 25:15 Module 06: Intelligence and National Security 17:02 6: Intelligence and National Security 17:02 Module 07: Legal Issues and Ethics 17:40 7: Legal Issues and Ethics 17:40 Module 08: Your Role, Responsibilities, and Functions as an Analyst 21:28 8: Your Role, Responsibilities, and Functions as an Analyst 21:28 Who is this course for? The target audience for the Intelligence Analyst Certification course is: Aspiring intelligence analysts seeking theoretical knowledge. Law enforcement professionals who are eager to deepen their understanding of intelligence. Students of political science or international relations who are aiming to expand their career horizons. Policymakers who are looking to leverage intelligence in strategic decision-making. Requirements There is no formal qualification for Intelligence Analyst Certification. Anyone from any background can enrol in this Intelligence Analyst Certification. Career path Some career paths related to this Intelligence Analyst Certification in the UK are: Intelligence Analyst National Security Analyst Law Enforcement Intelligence Officer Corporate Intelligence Consultant Political Risk Analyst Counterterrorism Analyst The average salary for these roles is £28K to £70k per year.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Are you looking to enhance your Data Analysis with Excel skills? If yes, then you have come to the right place. Our comprehensive course on Data Analysis with Excel will assist you in producing the best possible outcome by mastering the Data Analysis with Excel skills. The Data Analysis with Excel is for those who want to be successful. In the Data Analysis with Excel, you will learn the essential knowledge needed to become well versed in Data Analysis with Excel. Our Data Analysis with Excel starts with the basics of Data Analysis with Excel and gradually progresses towards advanced topics. Therefore, each lesson of this Data Analysis with Excel is intuitive and easy to understand. Why would you choose the Data Analysis with Excel from Compliance Central: Lifetime access to Data Analysis with Excel materials Full tutor support is available from Monday to Friday with the Data Analysis with Excel Learn Data Analysis with Excel skills at your own pace from the comfort of your home Gain a complete understanding of Data Analysis with Excel Accessible, informative Data Analysis with Excel learning modules designed by expert instructors Get 24/7 help or advice from our email and live chat teams with the Data Analysis with Excel bundle Study Data Analysis with Excel in your own time through your computer, tablet or mobile device. A 100% learning satisfaction guarantee with your Data Analysis with Excel Improve your chance of gaining in demand skills and better earning potential by completing the Data Analysis with Excel Data Analysis with Excel Curriculum Breakdown of the Data Analysis with Excel Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows Search for and Replace Data Use Proofing and Research Tools Working with Lists Sort Data Filter Data Query Data with Database Functions Outline and Subtotal Data Analyzing Data Apply Intermediate Conditional Formatting Apply Advanced Conditional Formatting Visualizing Data with Charts Create Charts Modify and Format Charts Use Advanced Chart Features Using PivotTables and PivotCharts Create a PivotTable Analyze PivotTable Data Present Data with PivotCharts Filter Data by Using Timelines and Slicers Working with Multiple Worksheets and Workbooks Use Links and External References Use 3-D References Consolidate Data Using Lookup Functions and Formula Auditing Use Lookup Functions Trace Cells Watch and Evaluate Formulas Automating Workbook Functionality Apply Data Validation Search for Invalid Data and Formulas with Errors Work with Macros Creating Sparklines and Mapping Data Create Sparklines MapData Forecasting Data Determine Potential Outcomes Using Data Tables Determine Potential Outcomes Using Scenarios Use the Goal Seek Feature Forecasting Data Trends CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Data Analysis with Excel helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Data Analysis with Excel. It is also great for professionals who are already working in Data Analysis with Excel and want to get promoted at work. Requirements To enrol in this Data Analysis with Excel, all you need is a basic understanding of the English Language and an internet connection. Career path The Data Analysis with Excel will enhance your knowledge and improve your confidence in exploring opportunities in various sectors related to Data Analysis with Excel. Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

Turn Your Dreams into Reality with the Excel Analyst - Excel Data Analysis and Visualisation Course Training course. This comprehensive Excel Analyst - Excel Data Analysis and Visualisation Course online course will equip you with the knowledge and skills you need to succeed in your chosen field. Whether you're a beginner or looking to take your career to the next level, this course has covered you. Key Learning Outcomes: Understanding the core concepts and theories in your field Building your knowledge and skills through practical, hands-on learning Developing the ability to think critically and solve problems effectively Enhancing your communication skills and the ability to work effectively with others Gaining a competitive edge in your career and reaching your full potential With a flexible online format that allows you to learn at your own pace, Excel Analyst - Excel Data Analysis and Visualisation Course training course offers a convenient and accessible way to boost your career prospects. So why wait? Enrol today and take the first step towards success! Vital Component of the Excel Analyst - Excel Data Analysis and Visualisation Course course: CPD Accredited Course Unlimited Retake Exam & Tutor Support Easy Accessibility to the Course Materials 100% Learning Satisfaction Guarantee Lifetime Access & 24/7 Support Self-paced online course Modules Covers to Explore Multiple Job Positions Transform your career with the Excel Analyst - Excel Data Analysis and Visualisation Course Bundle! Perfect your skills and stand out in the employment market with our comprehensive training program. Impress potential employers and add valuable expertise to your resume. Don't wait-enrol in the Excel Analyst - Excel Data Analysis and Visualisation Course Bundle now and take the first step towards a successful and fulfilling career! Course Outline: Modifying a Worksheet Working with Lists Analyzing Data Visualizing Data with Charts Using PivotTables and PivotCharts Working with Multiple Worksheets and Workbooks Using Lookup Functions and Formula Auditing Automating Workbook Functionality Creating Sparklines and Mapping Data Forecasting Data CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This course is the perfect fit for anyone seeking to start or advance in the Excel Analyst - Excel Data Analysis and Visualisation Course industry. Whether you're a beginner or looking to expand your knowledge, this comprehensive training will provide you with the essential skills and expertise to succeed. Requirements Join the Excitement-With this Excel Analyst - Excel Data Analysis and Visualisation Course course, there's no limit to what you can achieve. From day one, you'll be on your way to building a fulfilling career in this thriving field. No prior experience is required to enrol in this course. Career path Upon completion, you'll have the opportunity to pursue a variety of in-demand Excel Analyst - Excel Data Analysis and Visualisation Course jobs, with endless possibilities for growth and success. Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99 each

Duration 4 Days 24 CPD hours This course is intended for This basic course is for business data analysts who want to profile and assess data using Information Analyzer, also data quality analysts who need to measure data quality. Overview Analyze data structures to determine agreement with documented metadataDiscover data anomaliesIdentify invalid and incomplete data valuesDetermine potential primary keys to table structuresAdd business meaning to dataProduce deliverables that can be used by business users and ETL developersConfigure Information AnalyzerAdminister the Information Analyzer environmentUnderstand security considerations around data analysisUnderstand the methodology supporting data analysisUse Information Analyzer to analyze data content and structureUse Information Analyzer to construct data rules and utilize IBM-supplied data rule templates In this course, you will learn how to use the IBM InfoSphere suite to analyze data and report results to business users. Course Outline Information Analysis concepts Information Server overview Information Analyzer overview Information Analyzer Setup Column analysis Concepts Basic data profiling techniques in practice Data profiling techniques Primary key analysis Concepts Basic data profiling techniques in practice Foreign key and cross domain analysis Concepts Basic data profiling techniques in practice Baseline analysis Reporting and publishing Extending the meta data using Information Governance Catalog and Information Analyzer Data Rules and Metrics Additional course details: Nexus Humans KM803 IBM Information Analyzer Essentials v11.5 training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the KM803 IBM Information Analyzer Essentials v11.5 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

About Course Data Science and Data Analytics with Python: A Comprehensive Course for Beginners Unlock the power of data and gain insights that drive informed decisions with this comprehensive course on data science and data analytics with Python. This course is designed for beginners of all skill levels, with no prior programming experience required. You will learn the essential skills to embark on your data-driven journey, including: Data manipulation with NumPy and Pandas Data visualization with Matplotlib and Seaborn Statistical analysis with Python Machine learning and artificial intelligence You will also gain hands-on experience with real-world data projects, allowing you to apply your newfound knowledge to solve real-world problems. By the end of this course, you will be able to: Understand the fundamentals of data science and data analytics Apply Python to manipulate, visualize, and analyze data Use Python to build machine learning and artificial intelligence models Solve real-world data problems This course is the perfect launchpad for your data science journey. Whether you are looking to pivot your career, enhance your skill set, or simply quench your curiosity, this course will give you the foundation you need to succeed. Enroll today and start exploring the fascinating world of data science together! What Will You Learn? Understand the fundamentals of data science and data analytics Apply Python to manipulate, visualize, and analyze data Use Python to build machine learning and artificial intelligence models Solve real-world data problems Course Content Introduction to Python Data Science Introduction to Python Data Science Environment Setup Data Cleaning Packages Working with the Numpy package Working with Pandas Data science package Data Visualization Packages Working with Matplotlib Data Science package (Part - 1) Working with Matplotlib Data Science (Part - 2) A course by Uditha Bandara Microsoft Most Valuable Professional (MVP) RequirementsBeginners level knowledge for working with Data .Programming knowledge not required. Audience Beginners with no prior programming experience Anyone interested in learning data science and data analytics Audience Beginners with no prior programming experience Anyone interested in learning data science and data analytics

A course by Sekhar Metla IT Industry Expert RequirementsNo prior technical experience is required! All you need a computer!No SQL experience needed. You will learn everything you need to knowNo software is required in advance of the course (all software used in the course is free) Audience Beginner SQL, Data Science and Analytics - developers curious about SQL Career Anyone who wants to generate new income streams Anyone who works with data analytics, or databases! Anyone who wants to become Business intelligence developer Anyone who wants to start their own business or become freelance Anyone who wants to become a Data Science developer If you work in: marketing, finance, accounting, operations, sales, manufacturing, healthcare, financial services, or any other industry/function that collects information Someone who wants to learn skills that give them the potential to earn near SIX figures! Audience Beginner SQL, Data Science and Analytics - developers curious about SQL Career Anyone who wants to generate new income streams Anyone who works with data analytics, or databases! Anyone who wants to become Business intelligence developer Anyone who wants to start their own business or become freelance Anyone who wants to become a Data Science developer If you work in: marketing, finance, accounting, operations, sales, manufacturing, healthcare, financial services, or any other industry/function that collects information Someone who wants to learn skills that give them the potential to earn near SIX figures!

Duration 2 Days 12 CPD hours This course is intended for This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it's often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. Additional course details: Nexus Humans Python for Data Science Primer: Hands-on Technical Overview (TTPS4872) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Python for Data Science Primer: Hands-on Technical Overview (TTPS4872) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for This training is ideally suited for data analysts, IT professionals, and software developers who seek to augment their data processing and analytics capabilities. It will also benefit system administrators and data engineers who wish to harness Elastic Stack's functionalities for efficient system logging, monitoring, and robust data visualization. With a focus on practical application, this course is perfect for those aspiring to solve complex data challenges in real-time environments across diverse industry verticals. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll explore: New features and updates introduced in Elastic Stack 7.0 Fundamentals of Elastic Stack including Elasticsearch, Logstash, and Kibana Useful tips for using Elastic Cloud and deploying Elastic Stack in production environments How to install and configure an Elasticsearch architecture How to solve the full-text search problem with Elasticsearch Powerful analytics capabilities through aggregations using Elasticsearch How to build a data pipeline to transfer data from a variety of sources into Elasticsearch for analysis How to create interactive dashboards for effective storytelling with your data using Kibana How to secure, monitor and use Elastic Stack's alerting and reporting capabilities The Elastic Stack is a powerful combination of tools for techniques such as distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. Geared for experienced data analysts, IT professionals, and software developers who seek to augment their data processing and analytics capabilities, Working with Elasticsearch will explore how to use Elastic Stack and Elasticsearch efficiently to build powerful real-time data processing applications. Throughout the two-day hands-on course, you?ll explore the power of this robust toolset that enables advanced distributed search, analytics, logging, and visualization of data, enabled by new features in Elastic Stack 7.0. You?ll delve into the core functionalities of Elastic Stack, understanding the role of each component in constructing potent real-time data processing applications. You?ll gain proficiency in Elasticsearch for distributed searching and analytics, Logstash for logging, and Kibana for compelling data visualization. You?ll also explore the art of crafting custom plugins using Kibana and Beats, and familiarize yourself with Elastic X-Pack, a vital extension for effective security and monitoring. The course also covers essentials like Elasticsearch architecture, solving full-text search problems, data pipeline building, and creating interactive Kibana dashboards. Learn how to deploy Elastic Stack in production environments and explore the powerful analytics capabilities offered through Elasticsearch aggregations. The course will also touch upon securing, monitoring, and utilizing Elastic Stack's alerting and reporting capabilities. Hands-on labs, captivating demonstrations, and interactive group activities enrich your learning journey throughout the course. Introducing Elastic Stack What is Elasticsearch, and why use it? Exploring the components of the Elastic Stack Use cases of Elastic Stack Downloading and installing Getting Started with Elasticsearch Using the Kibana Console UI Core concepts of Elasticsearch CRUD operations Creating indexes and taking control of mapping REST API overview Searching - What is Relevant The basics of text analysis Searching from structured data Searching from the full text Writing compound queries Modeling relationships Analytics with Elasticsearch The basics of aggregations Preparing data for analysis Metric aggregations Bucket aggregations Pipeline aggregations Substantial Lab and Case Study Analyzing Log Data Log analysis challenges Using Logstash The Logstash architecture Overview of Logstash plugins Ingest node Visualizing Data with Kibana Downloading and installing Kibana Preparing data Kibana UI Timelion Using plugins