What is Analyze Data?
Analyze data or data analysis refers to the practice of studying, organizing, and transforming data to make it more useful. It also includes the cleansing of non-useful information which helps in better decision making regarding any particular matter. Analyze data is a practice that is used widely in the field of business, social sciences, and science.
How is Analyze Data used?
Zippia reviewed thousands of resumes to understand how analyze data is used in different jobs. Explore the list of common job responsibilities related to analyze data below:
- Develop queries/stored procedures to retrieve and analyze data for projects, program, or reports requiring sophisticated inferential techniques.
- Analyze data and reporting solutions to understand business impact, correlations/discrepancies, and to propose changes/alternate solutions.
- Analyze data and provide insight and recommendations on business decisions.
- Analyze data for critical applications.
- Collect, input, verify, correct, and analyze data to measure key performance indicator actual versus business objectives.
- Create reports and analyze data for patterns that indicate problems that need to be addressed or opportunities to investigate.
Are Analyze Data skills in demand?
Yes, analyze data skills are in demand today. Currently, 25,983 job openings list analyze data skills as a requirement. The job descriptions that most frequently include analyze data skills are business operations analyst, survey analyst, and marketing research coordinator.
How hard is it to learn Analyze Data?
Based on the average complexity level of the jobs that use analyze data the most: business operations analyst, survey analyst, and marketing research coordinator. The complexity level of these jobs is challenging.
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What jobs can you get with Analyze Data skills?
You can get a job as a business operations analyst, survey analyst, and marketing research coordinator with analyze data skills. After analyzing resumes and job postings, we identified these as the most common job titles for candidates with analyze data skills.
Business Operations Analyst
Job description:
A business operations analyst is an individual who identifies and solves issues related to the performance of the business operations. Together with the management and engineering departments, business operations analysts must analyze and review a vast amount of data to identify business opportunities. They must provide recommendations and updated policies so that they can improve the company's business performance. Business operations analysts are also required to create monthly reports and present them to upper management on their key findings and assessments.
- Provide Management
- Analyze Data
- Shared Services
- HR
- Business Operations
- Operational Efficiency
Marketing Research Coordinator
- Market Research
- Analyze Data
- Marketing Campaigns
- Research Data
- Research Projects
- Press Releases
Actuarial Internship
Job description:
The job of actuarial interns involves the roles of graduate actuaries featuring the challenges of a full-time actuary. Interns are given opportunities to work on projects from the offices of the firm or client. They improve the efficiency of the existing MS Excel workbooks through the automation of routine functions using VBA Macros. Their job includes the creation of comparative corporate financial statement reports on a monthly basis. Also, they maintain and document demographics every month.
- Competitive Analysis
- Analyze Data
- VBA
- SQL
- PowerPoint
- SAS
Education Research Analyst
Job description:
An education research analyst's main job is to monitor and collect data on the performance of various educational institutions and programs. The goal is to collect enough data to conduct a proper analysis and evaluation of every education program and determine areas that need improvement. The education system is a dynamic branch of society and constantly monitored to keep it up-to-date, current, and effective in molding the youth to become productive members of society.
- Analyze Data
- K-12
- Education Research
- Data Analysis
- Professional Development
- Mathematics
Labour Relations Analyst
- Collective Bargaining Agreements
- Collective Bargaining
- Arbitration
- Analyze Data
- Contract Negotiations
- Payroll
Research Scholar
Job description:
Research scholars are college students who perform on projects in a particular field for a university or organization. Generally, they work with professors and other professionals in the field of study and focus on discovering new information that can be produced in trade or academic journals. Also, they pursue intellectual and academic activities as well as may engaged in educating other researchers. They are usually paid a stipend for a set duration of time, and some may work outside the university.
- Analyze Data
- C++
- Original Research
- PCR
- Molecular Biology
- Data Analysis
Research Assistant/Technician
Job description:
A research assistant/technician is in charge of performing support tasks in laboratories, primarily to assist researchers. Among their responsibilities include conducting research and experiments under the researcher's directives and supervision, arranging and processing samples, maintaining records, organizing files, operating devices and equipment, and coordinating with different offices. They may also participate in preparing reports and research findings while adhering to the researcher's guidelines. Moreover, a research assistant/technician must prepare facilities and maintain its cleanliness according to the laboratory's rules and regulations.
- Patients
- Analyze Data
- Data Collection
- PCR
- Cell Culture
- Molecular Biology
Data Analysis Assistant
Job description:
A data analysis assistant works with data analysts and senior stakeholders to note data analysis requirements using these professionals' services. Also, data analyst assistants interpret data sets and monitor trends and patterns using statistical tools. These professionals correct primary and secondary data and reorganize it in a format that machines or human beings can understand.
- Data Analysis
- R
- Analyze Data
- Technical Support
- Behavior Analysis
- Tableau
Reporting Analyst
Job description:
As a reporting analyst, you are responsible for collecting relevant reports, analyzing raw data, writing, and delivering executive-ready qualitative and/or quantitative reports as per clients' requirements. The results collected will be communicated to managers or clients, who will then provide suggestions based on their findings. This person must have excellent quantitative & qualitative analytical skills, a strong eye for detail, strong organizational and multitasking abilities, and be able to work on tight deadlines. Intermediate to advanced knowledge of Excel is a must for this position.
- Power Bi
- Data Analysis
- Dashboards
- BI
- Analyze Data
- PowerPoint
Data Processing Analyst
Job description:
Data Processing Analysts are responsible for analyzing and maintaining the data systems of an organization. Their duties include interpreting data, analyzing statistical results, creating databases, identifying patterns from data sets, and undertake data filtering. They are also involved in preparing analytics reports, developing data visualizations, and mining data sets from primary or secondary sources. Data Processing Analysts also execute process automation, data validation, and documenting client's business requirements. They continuously monitor the performance metric of a project.
- Data Analysis
- Process Improvement
- Visualization
- Tableau
- Analyze Data
- Data Collection
Category Analyst
Job description:
A category analyst is responsible for evaluating the category management systems to improve efficiency and maximize the productivity of distribution departments and achieve the highest customer satisfaction. Category analysts coordinate with suppliers and third-party vendors, negotiate pricing contracts, research on current market trends for product selection, and maintain the adequacy of stock inventories. They also develop cost-reduction techniques by conducting data analysis and studying the current operational policies. A category analyst works closely with the marketing and sales team to identify business opportunities, implementing promotional techniques, and increase brand awareness to the public market.
- PowerPoint
- IRI
- Data Analysis
- Analyze Data
- POS
- Business Reviews
Research Associate R & D
Job description:
Research associates are employees who work in the company's research and development department. They are responsible for researching industry trends, product innovations, and even competitors' products. Research associates are usually fresh graduates or entry-level employees. They are exposed to the company's products and how each product came to be. They should be familiar with the company brand, as well as the company's vision and mission so that they are guided as they conduct research. Research associates research to further improve the current products and services of the company. They also help out in producing new products or innovating existing ones.
- Cell Culture
- Elisa
- Analyze Data
- Data Analysis
- Cell-Based Assays
- GMP
Biology Research Assistant
Job description:
A biological research assistant's role is to perform support tasks for biologists and researchers. Their responsibilities typically revolve around organizing samples and research documents, updating databases, reviewing documents, summarizing results into reports and presentations, handling calls and correspondence, coordinating with external parties, and running errands. There are also instances when a biological research assistant prepare laboratories and instruments, cleaning and sanitizing them as needed. Furthermore, one can also perform experiments and analyses under the supervision or directives of a more experienced researcher.
- Laboratory Equipment
- Laboratory Techniques
- Cell Culture
- Analyze Data
- Data Collection
- Animal Handling
Research Support Specialist
Job description:
A research support specialist is primarily in charge of performing administrative support and analytical tasks. Their responsibilities typically revolve around performing extensive research and analysis to gather necessary data, preparing and processing documentation on behalf of researchers, liaising with internal or external parties, troubleshooting problems, and maintaining records of all transactions. There are also instances when one must conduct studies, prepare manuscripts, develop strategies to optimize operations, and participate in implementing new research methods, all while adhering to the company or institution's policies and regulations.
- Research Support
- Data Collection
- Research Projects
- Analyze Data
- Biomedical
- Data Entry
Market Research Internship
Job description:
A Market Research Intern is responsible for conducting data and statistical analysis to evaluate market performance and identify opportunities to generate profits. Market Research Interns perform administrative duties under the supervision of a market research manager, such as writing and filing reports, organizing documents, researching trends, and designing participant surveys. A Market Research Intern must have excellent communication and analytical skills, especially in collecting accurate data and interpreting results.
- PowerPoint
- Data Analysis
- Research Projects
- Analyze Data
- Data Collection
- SPSS
Remote Sensing Analyst
Job description:
A remote sensing analyst is an individual who analyzes data measured from aircraft, satellites, or ground-based platforms to infer what it means about the world. Remote sensing analysts use tools such as analysis software, image analysis software, or a geographic information system to display the results of findings. They are involved in some fieldwork to confirm their findings by taking field measurements. Remote sensing analysts must also monitor the quality of information that is gathered and should develop databases.
- Troubleshoot
- Epic
- Analyze Data
- Data Collection
- Remote Sensing
- LiDAR
How much can you earn with Analyze Data skills?
You can earn up to $63,423 a year with analyze data skills if you become a business operations analyst, the highest-paying job that requires analyze data skills. Survey analysts can earn the second-highest salary among jobs that use Python, $73,489 a year.
| Job title | Average salary | Hourly rate |
|---|---|---|
| Business Operations Analyst | $63,423 | $30 |
| Survey Analyst | $73,489 | $35 |
| Marketing Research Coordinator | $57,307 | $28 |
| Actuarial Internship | $90,428 | $43 |
| Education Research Analyst | $62,634 | $30 |
Companies using Analyze Data in 2025
The top companies that look for employees with analyze data skills are Guidehouse, Ericsson, and Concorde Career Colleges. In the millions of job postings we reviewed, these companies mention analyze data skills most frequently.
| Rank | Company | % of all skills | Job openings |
|---|---|---|---|
| 1 | Guidehouse | 18% | 3,627 |
| 2 | Ericsson | 7% | 50 |
| 3 | Concorde Career Colleges | 6% | 622 |
| 4 | Oracle | 6% | 49,357 |
| 5 | Envision | 6% | 42 |
Departments using Analyze Data
The departments that use analyze data the most are marketing, sales, and finance.
| Department | Average salary |
|---|---|
| Marketing | $92,971 |
| Sales | $78,975 |
| Finance | $78,483 |
20 courses for Analyze Data skills
1. Analyze Data to Answer Questions
This is the fifth course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. In this course, you’ll explore the “analyze” phase of the data analysis process. You’ll take what you’ve learned to this point and apply it to your analysis to make sense of the data you’ve collected. You’ll learn how to organize and format your data using spreadsheets and SQL to help you look at and think about your data in different ways. You’ll also find out how to perform complex calculations on your data to complete business objectives. You’ll learn how to use formulas, functions, and SQL queries as you conduct your analysis. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary. By the end of this course, you will: - Learn how to organize data for analysis. - Discover the processes for formatting and adjusting data. - Gain an understanding of how to aggregate data in spreadsheets and by using SQL. - Use formulas and functions in spreadsheets for data calculations. - Learn how to complete calculations using SQL queries...
2. Analyze Survey Data with Tableau
Surveys are used in a variety of scenarios, both in businesses and in research. Companies are using them to better understand consumer insights and feedback, and researchers are going beyond the traditional uses to learn more about the world around us. Tableau can help visualize survey data of all kinds in a useful way—without needing advanced statistics, graphic design, or a statistics background. In this project, learners will learn how to create an account in Tableau and how to manipulate data with joins and pivots. Students will then learn how to create different kinds of visualizations, including tables, pie charts, and a stacked pie chart. This would be a great project for business and academic uses of survey data. This project is designed to be used by those somewhat familiar with Tableau and data visualizations. But the project can be accessible for those new to Tableau as well...
3. Analyzing Big Data with SQL
In this course, you'll get an in-depth look at the SQL SELECT statement and its main clauses. The course focuses on big data SQL engines Apache Hive and Apache Impala, but most of the information is applicable to SQL with traditional RDBMs as well; the instructor explicitly addresses differences for MySQL and PostgreSQL. By the end of the course, you will be able to • explore and navigate databases and tables using different tools; • understand the basics of SELECT statements; • understand how and why to filter results; • explore grouping and aggregation to answer analytic questions; • work with sorting and limiting results; and • combine multiple tables in different ways. To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements: • Windows, macOS, or Linux operating system (iPads and Android tablets will not work) • 64-bit operating system (32-bit operating systems will not work) • 8 GB RAM or more • 25GB free disk space or more • Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled; on Windows and Linux computers, you might need to enable it in the BIOS) • For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)...
4. Capstone: Analyzing (Social) Network Data
In this capstone project we’ll combine all of the skills from all four specialization courses to do something really fun: analyze social networks! The opportunities for learning are practically endless in a social network. Who are the “influential” members of the network? What are the sub-communities in the network? Who is connected to whom, and by how many links? These are just some of the questions you can explore in this project. We will provide you with a real-world data set and some infrastructure for getting started, as well as some warm up tasks and basic project requirements, but then it’ll be up to you where you want to take the project. If you’re running short on ideas, we’ll have several suggested directions that can help get your creativity and imagination going. Finally, to integrate the skills you acquired in course 4 (and to show off your project!) you will be asked to create a video showcase of your final product...
5. Managing, Describing, and Analyzing Data
In this course, you will learn the basics of understanding the data you have and why correctly classifying data is the first step to making correct decisions. You will describe data both graphically and numerically using descriptive statistics and R software. You will learn four probability distributions commonly used in the analysis of data. You will analyze data sets using the appropriate probability distribution. Finally, you will learn the basics of sampling error, sampling distributions, and errors in decision-making. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder...
6. Analyzing Time Series and Sequential Data
Using SAS Visual Forecasting and other SAS tools, you will learn to explore time series, create and select features, build and manage a large-scale forecasting system, and use a variety of models to identify, estimate and forecast signal components of interest...
7. Analyze Data in Azure ML Studio
Did you know that you can use Azure Machine Learning to help you analyze data? In this 1-hour project-based course, you will learn how to display descriptive statistics of a dataset, measure relationships between variables and visualize relationships between variables. To achieve this, we will use one example diabetes data. We will calculate its descriptive statistics and correlations, train a machine learning model and calculate its feature importance to see how features affect the label and visualize categorical data, as well as relationships between variables, in Jupyter notebook. In order to be successful in this project, you will need knowledge of Python language and experience with machine learning in Python. Also, Azure subscription is required (free trial is an option for those who don’t have it), as well as Azure Machine Learning resource and a compute instance within. Instructional links will be provided to guide you through creation, if needed, in the first task. If you are ready to learn how to analyze data, this is a course for you! Let’s get started!...
8. Analyzing and Visualizing Data in Looker
In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making...
9. Mining and Analyzing LinkedIn Data
LinkedIn is a social network focused on professional experience in order to generate connections and relationships between professionals from different areas. Professionals can provide profissional skills and search for jobs by connecting with people around the world. For example, if you would like to work with Data Science you can connect with companies and people who work in this field, increasing your chances of getting a job. On the other hand, companies are able to search for candidates according to the curriculum and skills provided by users. In 2017, LinkedIn established itself as the largest business platform and an important strategic tool for both professionals and companies. It is important that professionals know how to use the data of this social network in their favor. LinkedIn provides some datasets related to your profile, in which it is possible to apply Data Science and Analysis techniques to extract important and interesting insights about our network of connections. We can answer questions like this: What are the main positions of the people who are connected to us? Which companies are sending invitations to our profile? What is the location of our contacts? Is our LinkedIn network made up of people and companies related to our job? Are the companies I want to work for sending invitations to my profile? These and other questions can be answered during this course, so you can analyze if your network is in line with what you want professionally. Below you can see the main topics that will be implemented step by step: Extract data from your LinkedIn profile using the LinkedIn API and. csv files. If you do not have LinkedIn, you will be able to follow the course using the data about my profileExtract and analyze connections between users, invitations and text messagesGenerate fake data to mask real informationExplore and visualize data related to your contacts' companies and job titlesUse Levenshtein distance, n-gram similarity and Jaccard distance to measure similarity between stringsCluster contacts based on similarity between positions, as well as generate HTML views to improve data presentationUse location APIs to extract latitude and longitude of contacts to capture the city and country they liveView the location of contacts dynamically with Google Earth and the Basemap libraryCluster contacts using k-means algorithmApply natural language processing techniques to analyze your LinkedIn text messagesGenerate word cloud to view the most frequent termsExtract named entities from your text messagesCreate a sentiment classifier to extract the polarity from LinkedIn messagesDuring the course, we will use the Python programming language and Google Colab, so you do not need to spend time installing the stuff on your own machine. You will be able to follow the course with a browser and an Internet connection! This is the best course if this is your first contact with social media data analysis!...
10. How to analyze Qualitative data
I love the presenter's obvious passion for the subject. He talks about real issues which I too have encountered. I find this both affirming and reassuring. Thank you.⭐⭐⭐⭐⭐Jarek, Thank you for your course- it helped tremendously in conceptually griping the qualitative approach in applying it to my research project.⭐⭐⭐⭐⭐Thanks to this course, I became aware of the main concepts, stages and steps involved in the analysis of qualitative data. The course is presented in a wonderful way and concepts are clearly explained by the tutor. I have learnt a lot from this course. keep up the good work Dr⭐⭐⭐⭐⭐In this course, I will teach you how to analyse qualitative data. Too often qualitative data analysis is equated with simply coding it. As I will show you in this course, however, data analysis starts way before coding, and finishes way after the coding is done. I love analyzing qualitative data and my personal aim, apart from equipping you with the knowledge required to analyse your data, is to help you understand how enjoyable a process it can be. I also want you to realize that this is not like science - this is a flexible, dynamic and subjective process, and how you analyse your data will depend, above all, on your own decisions and interpretations, your aims and your research questions. Please watch the video and scroll down to the course curriculum to learn more about the course content, and feel free to ask me questions if you are not sure whether this course is for you. Otherwise, see you in the course!:)Dr K (Jarek)...
11. Analyzing and Visualizing Data the Google Way
This learning experience guides you through the process of utilizing various data sources and multiple Google Cloud products (including BigQuery and Google Sheets using Connected Sheets) to analyze, visualize, and interpret data to answer specific questions and share insights with key decision makers...
12. Analyze Box Office Data with Seaborn and Python
Welcome to this project-based course on Analyzing Box Office Data with Seaborn and Python. In this course, you will be working with the The Movie Database (TMDB) Box Office Prediction data set. The motion picture industry is raking in more revenue than ever with its expansive growth the world over. Can we build models to accurately predict movie revenue? Could the results from these models be used to further increase revenue? We try to answer these questions by way of exploratory data analysis (EDA) in this project and the next. The statistical data visualization libraries Seaborn and Plotly will be our workhorses to generate interactive, publication-quality graphs. By the end of this course, you will be able to produce data visualizations in Python with Seaborn, and apply graphical techniques used in exploratory data analysis (EDA). This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions...
13. Practical Data Science: Analyzing Stock Market Data with R
In this class, we will explore various technical and quantitative analysis techniques using the R programming language. I will code as I go and explain what I am doing. All the code is included in PDFs attached to each lecture. I encourage you to code along to not only better understand the concepts but realize how easy they are. What We'll CoverEasily access free, stock-market data using R and the quantmod packageBuild great looking stock charts with quantmodUse R to manipulate time-series dataCreate a moving average from scratchAccess technical indicators with the TTR packageCreate a simple trading systems by shifting time series using the binhf packageA look at trend-following trading systems using moving averagesA look at counter-trend trading systems using moving averagesUsing more sophisticated indicators (ROC, RSI, CCI, VWAP, Chaikin Volatility)Grouping stocks by theme to better understand themFinding coupling and decoupling stocks within an indexWhat This Class Isn'tThis class isn't about telling you how to trade or revealing secret trading methods, but to show how easy it is to explore the stock market using R so you can come up with your own ideas...
14. Excel functions to analyze and visualize data
Welcome to our first ever course Excel functions to analyze and visualize data We are glad to meet you. If only we could shake hands! Are you wondering how is this course going to be useful to you? Hey, did you watch the promo video? If not, please do. If you are looking to learn Microsoft Excel basics, this course will teach you exactly that. Look, Microsoft Excel is ubiquitous. It is used in almost every job we do in today's world. So your job will also possibly require you to do analysis on large heaps of data. Our course does exactly that - we make you job ready for your prospective project / daily work. What makes our course different from others? Our course content is unique - you learn exactly what you are required to do in your daily work. You get 1.5 hours of crisp synthesized practical real life illustrations of all concepts. You will be carrying out the real life illustrations along with the instructor. Same set up as the instructor. All illustration spreadsheets are shared. It's almost like as if somebody is guiding you in person to carry out the various analysis. You are going to love our instructor's teaching style. He makes it very engaging and fun learning experience. You will have practice assignments / course challenges with varying difficulty levels to test your learning from the course. Our support team responds to any course queries within 24 hours of your request. And of course, the price is competitive. What will you learn in this course? An overview of Microsoft Excel functions (Large) Data Analysis techniques and Data visualization in Excel This one single course will be comprehensive to cover the basic knowledge of Excel required for day to day work You can watch the FREE course previews in the CURRICULUM section. Read through the entire CURRICULUM section if you can. All modules with details of lectures are provided. What next? Well, we sincerely hope to see you inside the course. We wish you well and good luck. Still confused? Don't hesitate to reach out...
15. Scrape and analyze data analyst job requirements with Python
In this project, you’ll help a recruitment agency improve its job vacancy sourcing by using Python’s web-scraping capabilities to extract job postings from multiple sites. This task will require you to write a Python script to extract job posting data from the source site and save it to a comma separated values (CSV) file. Your work will help the agency provide clients with with relevant job openings more quickly, giving them a competitive advantage over other applicants. There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers. ROLE: Data Analyst SKILLS: Python PREREQUISITES: variables, data types, loops, functions, and file input/output in Python web scraping techniques data cleaning, preprocessing, and visualization techniques BeautifulSoup, Git, Jupyter Notebook...
16. SQL with PostgreSQL for Beginners: Analyze Manipulate Data
SQL stands for Structured Query Language. It is one of the most in-demand tech skills in the world. What Can SQL do?SQL lets you access and manipulate databasesSQL can execute queries against a databaseSQL can retrieve data from a databaseSQL can insert records in a databaseSQL can update records in a databaseSQL can delete records from a databaseSQL can create new databasesSQL can create new tables in a databaseSQL can create stored procedures in a databaseSQL can filter data returned from a databaseSQL can sort data returned by a database. SQL can be used to truncate and drop tables. PostgreSQL is a powerful, open source object-relational database management system. PostgreSQL is an advanced, enterprise-class, and open-source relational database system. PostgreSQL supports both SQL (relational) and JSON (non-relational) querying. PostgreSQL is a highly stable database backed by more than 20 years of development by the open-source community. PostgreSQL is used as a primary database for many web applications as well as mobile and analytics applications. What You Will LearnPerform CRUD OperationsPostgreSQL Database ObjectsDatabase ConceptsCreating a database using PostgreSQL GUICreating tables with PostgreSQL GUI and SQL CommandsInserting Data into tablesQuery and read data stored inside a tableFilter and Sort data from a tableUsing Sub query to retrieve dataUpdating existing data stored inside a databaseQuery and eliminate duplicate recordsDeleting records stored inside databaseTruncating a database tableDropping a database tableImplementing Stored ProcedureJoining and querying data from multiple tablesUsing various aggregate functions and grouping dataUsing various Operators to query dataUsing various Analytic Functions...
17. Kibana Masterclass - Capture, Analyze and Visualize Data
What is Kibana ?Kibana is one of the tools belonging to the ELK stack. It is one of the most popular tools to analyze and visualize big amount of data. This data maybe from Application Logs, Infrastructure Metrics or IOT devices. What does this course cover ?I have been using Kibana for visualizing and creating dashboard for multiple years , and have tried to keep this course as practical as possible. This is going to be a hands-on course wherein you would learn and understand various ways of ingesting data into Kibana and creating meaningful dashboards for types of roles in the company. We are going to gain the knowledge in the following organized stepsAdding data to Kibana Explore the data using Kibana Discover Create various types of visualizations ( pie chart , bar chart , line chart and more ) based on the type of dataAlso covering data aggregation and filteringWe move on to Monitoring and analyzing metrics of applications and computers , and setting up email alertsFinally we also see how to build search engine for our website using App search and web crawlers As a bonus , I will also show you how you could leverage the ELK stack to build a logging system for your applications. We will be using an actual web application that I have developed and connect it to Kibana, we will then monitor and check the performance of our website. This is the most in depth course on Kibana on Udemy , which will give your the knowledge to explore and implement Kibana at the fullest. Finally, I am very active on Q & A and would be happy to assist you throughout the course. Wish you all the best and happy learning...
18. MS Excel Exam Guide: Analyzing and Visualizing Data
Microsoft Excel is one of the most important software programs ever created. Businesses large and small, in countries all around the world, run off of systems and processes built on and around Excel. With so many people using Excel as part of their day-to-day jobs, it is more important than ever for you to stand out from the crowd and certify your Excel skills so you can contribute and be entrusted with these business-critical opportunities. Enter this course. Designed directly off the study guides and outlines for the Excel 70-779 Exam, this course provides not only the theory but also the practical and foundational skills needed to pass the certification exam and stand out from the crowd. Not only will you be well prepared for the exam, but you'll also build out a skill set that will be in demand for years to come. When you're ready to professionally certify your Excel skills, this is the course for you...
19. Azure MasterClass: Analyze Data With Azure Stream Analytics
As the old adage says: information is powerFor some time now, and with the boom of the Internet and social media, data is playing an increasingly bigger role in all organizations, which are continuously looking for solutions that will enable to capture data from different internet sources and analyze it in an as close to real-time rate as possible. This has caused organizations to invest in building solutions that not only can obtain and review data in depth and in real-time, but also save time in scheduling recurrent tasks and integrate with other systems seamlessly, allowing for scalability and availability while minimizing faults and latency. Having the right information in time is a now a critical aspect to making strategic business decisions. This is where Azure Stream Analytics comes in, to provide an effective solution to this business need. Azure Stream Analytics, or ASA, is an independent, cost-effective, and near real-time processing agent that enables you to view and explore streaming data at a high-performance level. Using this portal, you can set up data streaming computations from devices, sensors, web sites, social media, applications, infrastructure systems, and more with just a few clicks. Do you know what it takes to design and deploy sophisticated data analytics pipelines which can transform data into actionable insights and predictions in near real-time? How does one go about scaling this data analysis infrastructure? How to Easily develop and run massively parallel real-time analytics on multiple IoT or non-IoT streams of data using simple SQL like language.? These are some of the fundamental problems data analysts and data scientists struggle with on a daily basis. This course teaches you how to design, deploy, configure and manage your real time scalable data analytics in the Azure cloud resources with Azure Stream Analytics. The course will start with basics of ASA and query setup, and then moves deeper into details about ASA and its other integrated services so you can make the most out of the functionalities you have available in this tool. If you're serious about building scalable, flexible and robust data analytics With no infrastructure to manage, where you can process data on-demand, scale instantly, and only pay per job, then this course is for you. These data analytics and Cloud Computing skills are in high demand, but there's no easy way to acquire this knowledge. Rather than rely on hit and trial method, this course will provide you with all the information you need to get started with your Azure data analytics projects. Startups and technology companies pay big bucks for experience and skills in these technologies. They demand data engineers to provide them real time actionable analysis - and in turn, you can demand top dollar for your abilities. Do you want the skills and be highly sought after? Do you want your career to touch cloud 9? Did you answer, "Absolutely" to that question? If so, then our new training program Azure Masterclass: Analyze your data with Azure Stream Analytics is for you. Look, if you're serious about becoming an expert data engineer and generating a significant income for you and your family, it's time to take action. Imagine getting that promotion which you've been promised for the last two presidential terms. Imagine getting chased by recruiters looking for skilled and experienced engineers by companies that are desperately seeking help. We call those good problems to have...
20. Analyze Huge Data with Ease Using Microsoft Excel Filters!
WHAT'S YOUR STORY? Are you a business professional needing to up-skill?Are you struggling to get a pay-rise and/or promotion?Are you a recent graduate with an empty looking resume and no job experience?Have you recently been laid off, fired or had a contract end? If you answered 'yes' to any of the above then having "Expert Microsoft Office Skills" will get you closer to your goal of either landing your first job, a new job or progressing further in your current role. Here's why. The job market has never been more volatile. Statistically, people are changing jobs more often now than they ever have before and that also means people are also losing jobs to newcomers who are far more skilled. So if you're not up-skilling, you're falling behind. It's scary I know. I've experienced this myself. A study released by Microsoft and the IDC showed that among 14.6 million job postings, proficiency in Microsoft Office was ranked 2nd as the most desired skills by employers leading up to 2020. Microsoft Office proficiency ranked higher than Project Management skills, Sales Experience, Time Management, Analytical Skills, Interpersonal Skills and Work Ethics. This is because we live in the digital age, meaning employers are looking for proficient data handlers who process data faster, are more data-organised and can communicate effectively via digital channels. These are skills everyone should have no matter the discipline because they are transferable skills. It makes you more adaptable and more valuable in the long-term. This brings us back to Microsoft Office. It is the oldest, most well-known, most affordable and most trusted data management tool available and hence everyone uses it. So to be noticed and taken seriously in your job or job application, proficiency in these programs is compulsory. ONLINE TRAINING AND THE MOST COMMON PROBLEMS One of the most common problems with online learning content is that there is so much of it now and it's difficult to know where to start or who to turn to. Many go the YouTube route and piece together videos from hundreds of tutorials from hundreds of tutors hoping to become an expert at the end of it all. This simply won't happen and will just waste your time. Many take the route you're about to take, they decide to enroll in an online training course. Many charge hundreds, sometimes thousands of dollars for their courses which is simply unaffordable for university students, recent graduates, the unemployed or those looking for a career change. That is the reason why I have decided to keep this course as low as possible even though I'm offering substantially more content than most of my competitors here on Udemy. COURSE DELIVERY STYLE I have been using Microsoft Office for over 20 years. I know the in's and out's and the simplest ways of doing things. My delivery philosophy is simple, if I can't get a 6 year old to follow along and understand, than I'm not teaching correctly. I hate complicated language and so do you. Nobody likes trainers who focus on impressing rather than teaching and giving value to students. That is also why my lecture videos are as short as can be and divided into small sections for easy consumption. So you won't get unnecessary chit chat or nonsense. I also assume that all my students are near-sighted and as such, I use a special software tool that allows me to draw on the screen to show exactly what I'm about to press as well as zoom in on small area's so you don't miss a thing. WHAT YOU'LL LEARN IN THIS COURSE This is an technique in Excel which allows you to control, reorganize, filter, trim and manipulate large sets of data with ease. Say goodbye to the days of scrolling through long lists of data. With this function you can you let Excel do the hard work. You tell Excel what type of filtering you want, and Excel does the rest. I'll be covering in great detail how to set up your data for the filter as well as introducing a tracking technique which preserves the integrity of your data Then I'll show you how to re-organise data alphabetical, by colour, by value, by partial match, by ranking, by percentage and many more. We'll then finish the course off with combinations via the use of Conditional Formatting, Dynamic Charts and Array Fill. ABOUT ME Member of the Udemy CouncilCo-Founded Paperclip Learning which teaches Microsoft OfficeOver 60,000 studentsOver 130,000 enrollmentsOver 5,000 Positive ReviewsOver 20 courses on Udemy Teaching is my passion and my creative outlet. I have been using the Microsoft Office package since I was a child and have been using it consistently throughout my life. My teaching experiences span from teaching primary school students, high school students, university graduates and business professionals. Professionally, I am trained in Aerospace Engineering, Database Design and Business Analytics. TESTIMONIALS Yu Hui Jun Yu - The courses are simply amazing and I can learn them rapidly. The hints presented were also very useful. I like the 'mini-lesson' format. Fast and efficient. The instructor's direction is very detailed and easy to understand. I can immediately start using this program. Thanks! Narayanan Krishnamoorthy - Perfect and to the point... the instructor doesn't waste time and gets to the point quickly!! Lala Darchinova - I've been looking for this kind of course for ages! And finally I find it. Short, comprehensive and absolutely interesting! Thank you for the work you are doing. Spencer Berkman - Extremely knowledgeable and clear on instructions. E Frank - Simple to learn techniques and instructor made it all really easy. Thank you! Parth Gandhi - I learned techniques in a very short time... no need to google and waste time finding the perfect approach...