The difference between MS Excel, MS Access, MySQL, Cloud ML and AI

Definitions of each Application:

Microsoft Excel:
Microsoft Excel is used to displays the data in horizontal and vertical rows. The data are usually stored in the cells. We have an option of formulas in the Excel that can be used for data, data analysis, statistical analysis, and its place of storage.

  • You can even add any charts, graphics, etc. to make it more presentable.
  • Excel locks the whole spreadsheet once it is accessed.
  • An Excel document is referred to as a workbook and each of these workbooks must contain at least one worksheet.

Microsoft Access:
Microsoft Access is a database program, it uses unique ID numbers and an editable list of data to store details on large amounts of items, i.e., you could use this program to store large amount of data.

  • Access is designed to have multiple users working in the same DB files along with the various safety precautions items to help protect the data such as record level locking.
  • The database created in Access is saved with a .mdb extension.
  • Data is stored in tables.
  • Each field of a table can be associated with certain constraints like only allowing an alphanumeric value or different datatypes.
  • Like any other relational database, it works on the principles of tables, fields, and relationships. It supports different kinds of datatypes – numbers, dates, texts, etc.

MySQL:

MySQL is an open-source relational database management system based on SQL – Structured Query Language. The application is used for a wide range of purposes, including data warehousing, e-commerce, and logging applications.

  • Data is stored in tables.
  • Each field of a table can be associated with certain constraints like only allowing an alphanumeric value or different datatypes.
  • Like any other relational database, it works on the principles of tables, fields, and relationships. It supports different kinds of datatypes – numbers, dates, texts, etc.
  • MySQL is easy to use.
  • It is secure.
  • Client/ Server Architecture.
  • Free to download.
  • It is scalable.
  • High speed.
  • High Flexibility.

Cloud ML:

The Cloud ML Engine is a hosted platform to run machine learning training jobs and predictions at scale. The service can also be used to deploy a model that is trained in external environments. Cloud ML Engine automates all resource provisioning and monitoring for running the jobs.

The cloud makes intelligent capabilities accessible without requiring advanced skills in artificial intelligence or data science. AWS, Microsoft Azure, and Google Cloud Platform offer many machine learning options that don’t require deep knowledge of AI, machine learning theory, or a team of data scientists.

  • The cloud’s pay-per-use model is good for bursty AI or machine learning workloads.
  • The cloud makes it easy for enterprises to experiment with machine learning capabilities and scale up as projects go into production and demand increases.
  • The cloud makes intelligent capabilities accessible without requiring advanced skills in artificial intelligence or data science.
  • AWS, Microsoft Azure, and Google Cloud Platform offer many machine learning options that don’t require deep knowledge of AI, machine learning theory, or a team of data scientists.

Cloud AI:

The AI cloud, a concept only now starting to be implemented by enterprises, combines artificial intelligence (AI) with cloud computing. An AI cloud consists of a shared infrastructure for AI use cases, supporting numerous projects and AI workloads simultaneously, on cloud infrastructure at any given point in time.

  • Data Mining.
  • Agile Development.
  • Reshaping of IT Infrastructure.
  • Seamless Data Access.
  • Analytics and Prediction.
  • Cloud Security Automation.
  • Cost-Effective.
MS ExcelMS AccessMySQLCloud MLCloud AI
Microsoft Excel is an application that uses spreadsheets to create charts, graphs, tabular models.Microsoft Access is an application that acts as a database program. Access deal with database program by collecting, sorting, and manipulating data.MySQL is an open-source relational database management system based on SQLThe Cloud ML Engine is a hosted platform to run machine learning training jobs and predictions at scale.An AI cloud consists of a shared infrastructure for AI use cases, supporting numerous projects and AI workloads simultaneously, on cloud infrastructure at any given point in time.
It is used for spreadsheets,  statistical and financial calculations.   Excel helps in performing sophisticated what-if analysis operations on your data, such as statistical, engineering, and regression analysis.It is used for storing and manipulating large amounts of information.   Access do not perform what-if analysis.The application is used for a wide range of purposes, including data warehousing, e-commerce, and logging applications.The service can also be used to deploy a model that is trained in external environments. Cloud ML Engine automates all resource provisioning and monitoring for running the jobs.Enterprises use the power of AI-driven cloud computing to be more efficient, strategic, and insight-driven. AI can automate complex and repetitive tasks to boost productivity, as well as perform data analysis without any human intervention. IT teams can also use AI to manage and monitor core workflows.
Microsoft Excel is easy to learn.Microsoft access is quite hard to learn.   Access that needs programming knowledge for some part.  MySQL is easy to use.The pay-per-use model further makes it easy to access more sophisticated capabilities without the need to bring in new advanced hardware.Cloud AI Platform is a service that enables user to easily build machine learning models, that work on any type of data, of any size.
The storage capacity is less since excel isn’t built for storing data.The storage capacity is more since access is mainly built for storing, sorting, and manipulating databases.MySQL stores data in files in your hard disk. The maximum size of MySQL table is 65536 terabytes.This storage service provides petabytes of capacity with a maximum unit size of 10 MB per cell and 100 MB per row. 1024 Petabytes of data.1024 Petabytes of data. The larger the RAM the higher the amount of data it can handle hence faster processing. 16GB RAM and above is recommended for most deep learning tasks.
Excel is less flexibility as compared to access.Access has more flexibility as compared to excel.High Flexibility.  High Flexibility and Cost Effective.Seamless Data Access. High Flexibility and Cost Effective.
It works on the data model of a non-relational or flat worksheet.It works on the model of multiple relational tables and sheets.MySQL is a Relational Database Management System (RDBMS). The logical model, with objects such as databases, tables, views, rows, and columns, offers a flexible programming environment.Cloud ML Engine is used to train machine learning models in TensorFlow and other Python ML libraries (such as scikit-learn) without having to manage any infrastructure.In Artificial Intelligence, the Decision Tree (DT) model is used to arrive at a conclusion based on the data from past decisions. 
It locks the entire spreadsheet.It locks data at the record level.MySQL uses table-level locking in all storage engines except InnoDB meaning that table-level locking is used for tables running the MyISAM, MEMORY and MERGE storage engines, permitting only one session to update tables at a time.Cloud DLP – Data Loss Prevention provides tools to classify, mask, tokenize, and transform sensitive elements to help you better manage the data that you collect, store, or use for business or analytics.Cloud DLP – Data Loss Prevention provides tools to classify, mask, tokenize, and transform sensitive elements to help you better manage the data that you collect, store, or use for business or analytics.
Excel is good for short term solutions and small-scale projectsAccess is good for long term solutions and large-scale projects.MySQL is ideal for storing application data, specifically web application data. As MySQL is a relational database, it’s a good fit for applications that rely heavily on multi-row transactions.The cloud makes intelligent capabilities accessible without requiring advanced skills in artificial intelligence or data science.  The cloud makes intelligent capabilities accessible without requiring advanced skills in artificial intelligence or data science.  
Microsoft ProductMicrosoft ProductOracle ProductGoogle, Amazon, Microsoft, and IBMGoogle, Amazon, Microsoft, and IBM
   ML’s aim is to improve accuracy without caring for success.

The goal of AI is to increase the chances of success.
   ML is the way for the computer program to learn from experience.AI is a computer program doing smart work.
   The ML’s goal is to keep learning from data to maximize the performance.The future goal of AI is to stimulate intelligence for solving highly complex programs.
   ML allows the computer to learn new things from the available information.AI involves decision-making.
   ML looks for the only solution.AI looks for optimal solutions.
     

The difference between MS Excel and MS Access

Microsoft Excel:
Microsoft Excel is used to displays the data in horizontal and vertical rows. The data are usually stored in the cells. We have an option of formulas in the Excel that can be used for data, data analysis, statistical analysis, and its place of storage.

  • You can even add any charts, graphics, etc. to make it more presentable.
  • Excel locks the whole spreadsheet once it is accessed.
  • An Excel document is referred to as a workbook and each of these workbooks must contain at least one worksheet.

Microsoft Access:
Microsoft Access is a database program, it uses unique ID numbers and an editable list of data to store details on large amounts of items, i.e., you could use this program to store large amount of data.

  • Access is designed to have multiple users working in the same DB files along with the various safety precautions items to help protect the data such as record level locking.
  • The database created in Access is saved with a .mdb extension.
  • Data is stored in tables.
  • Each field of a table can be associated with certain constraints like only allowing an alphanumeric value or different datatypes.
  • Like any other relational database, it works on the principles of tables, fields, and relationships. It supports different kinds of datatypes – numbers, dates, texts, etc.
MS ExcelMS Access
Microsoft Excel is an application that uses spreadsheets to create charts, graphs, tabular models.Microsoft Access is an application that acts as a database program. Access deal with database program by collecting, sorting, and manipulating data.
It is used for spreadsheets,  statistical and financial calculations.   Excel helps in performing sophisticated what-if analysis operations on your data, such as statistical, engineering, and regression analysis.It is used for storing and manipulating large amounts of information.   Access do not perform what-if analysis.
Microsoft Excel is easy to learn.Microsoft access is quite hard to learn.   Access that needs programming knowledge for some part.  
The storage capacity is less since excel isn’t built for storing data.The storage capacity is more since access is mainly built for storing, sorting, and manipulating databases.
Excel is less flexibility as compared to access.Access has more flexibility as compared to excel.
It works on the data model of a non-relational or flat worksheet.It works on the model of multiple relational tables and sheets.
It locks the entire spreadsheet.It locks data at the record level.
Excel is good for short term solutions and small-scale projectsAccess is good for long term solutions and large-scale projects.
Microsoft ProductMicrosoft Product

Conclusion:

Microsoft Excel and Access are great tools for data exploration of structured and unstructured data, which has earned a top spot amongst tools used by Data Scientists and Analysts.

The difference between MS Access and MySQL

Microsoft Access:
Microsoft Access is a database program, it uses unique ID numbers and an editable list of data to store details on large amounts of items, i.e., you could use this program to store large amount of data.

  • Access is designed to have multiple users working in the same DB files along with the various safety precautions items to help protect the data such as record level locking.
  • The database created in Access is saved with a .mdb extension.
  • Data is stored in tables.
  • Each field of a table can be associated with certain constraints like only allowing an alphanumeric value or different datatypes.
  • Like any other relational database, it works on the principles of tables, fields, and relationships. It supports different kinds of datatypes – numbers, dates, texts, etc.

MySQL:

MySQL is an open-source relational database management system based on SQL – Structured Query Language. The application is used for a wide range of purposes, including data warehousing, e-commerce, and logging applications.

  • Data is stored in tables.
  • Each field of a table can be associated with certain constraints like only allowing an alphanumeric value or different datatypes.
  • Like any other relational database, it works on the principles of tables, fields, and relationships. It supports different kinds of datatypes – numbers, dates, texts, etc.
  • MySQL is easy to use.
  • It is secure.
  • Client/ Server Architecture.
  • Free to download.
  • It is scalable.
  • High speed.
  • High Flexibility.
MS AccessMySQL
Microsoft Access is an application that acts as a database program. Access deal with database program by collecting, sorting, and manipulating data.MySQL is an open-source relational database management system based on SQL
It is used for storing and manipulating large amounts of information.   Access do not perform what-if analysis.The application is used for a wide range of purposes, including data warehousing, e-commerce, and logging applications.
Microsoft access is quite hard to learn.   Access that needs programming knowledge for some part.  MySQL is easy to use.
The storage capacity is more since access is mainly built for storing, sorting, and manipulating databases.MySQL stores data in files in your hard disk. The maximum size of MySQL table is 65536 terabytes.
Access has more flexibility as compared to excel.High Flexibility.  
It works on the model of multiple relational tables and sheets.MySQL is a Relational Database Management System (RDBMS). The logical model, with objects such as databases, tables, views, rows, and columns, offers a flexible programming environment.
It locks data at the record level.MySQL uses table-level locking in all storage engines except InnoDB meaning that table-level locking is used for tables running the MyISAM, MEMORY and MERGE storage engines, permitting only one session to update tables at a time.
Access is good for long term solutions and large-scale projects.MySQL is ideal for storing application data, specifically web application data. As MySQL is a relational database, it’s a good fit for applications that rely heavily on multi-row transactions.
Microsoft ProductOracle Product

Data Analyst

Lead Data Analyst
San Francisco, CA
Full time
Brief description of your team function: 
The core charter of Credit data services is to build best-in-class data solutions to help bring value to the Credit business. We are looking for an individual who is eager to explore new data, while at the same time is proficient enough in existing data to support business stakeholders looking to leverage it in their last-mile solutions. 
The role will involve understanding business requirements, conducting hand-on business systems analysis and translating requirements into technical specifications to produce scalable and consistent solutions.  
The role will be responsible for supporting global stakeholder departments, working domain leads and data citizens across different GEO’s such as Americas, EMEA, and Asia Pacific.  This position requires interaction with geographically disbursed business and technical teams requiring the candidate be a self-starter with strong written/verbal communication skills, leadership qualities and project/task management skills. 

Breakdown of Day to Day tasks  

  • 30% Meeting business stakeholders to gather/discuss business requirements 
  • 20% Business systems and data analysis
  • 20% Documenting/Building technical specification
  • 30% Working with engineering team development satisfies business functional requirements 

Top 3 hard skills, stack ranked 

  • Business systems analysis, data analysis (Teradata, Oracle, Hadoop), problem-solving  
  • Data modeling & data solutions architecture 
  • Communication skills 

What is going to make someone stand out as the best 

  • Bachelor’s degree in computer science or engineering discipline with a strong quantitative aptitude 
  • Ability to work with business leads, business stakeholders, subject matter experts and technical staff to gather and develop business needs in the form of technical requirements 
  • Identifying and refining current and future‐state business processes by performing deep dive analysis of current state and propose future state solutions effectively using clear and precise documentation 
  • Motivation to understand business processes and data platforms in order to design/deliver scalable data solutions to support customer needs 
  • Good understanding of database principles and advanced SQL in order to perform complex analysis 
  • Expert understanding of data modelling concepts, experience with data modelling and generating metadata to support relational & non-relational database implementations; experience building logical and physical data models. 
  • Good understanding of distributed systems (Teradata, Hadoop), data movement and optimizing ETL processing of extremely large datasets with specified SLAs. 
  • Collaborate closely with engineering team and provide ongoing support to help implement end user requirements 
  • Ensure the consistency and quality of data solutions completed by engineering team. 
  • Prior knowledge of any analytical visualization tools like Tableau, MSTR is desirable 
  • Document data solutions for easy business consumption. 
  • Strong communication skills, both written and verbal, and skilled at adjusting communication style/vocabulary to an audience’s role/function and technical familiarity 

How will you determine if the individual is performing well? 

  • Documentation of requirements/needs gathered from business teams 
  • Communications/updates to management and project team members 
  • Functional specs and other documentation given as requirements to engineering teams 
  • Ability to identify and communicate effort, risks and dependencies to project team members/stakeholders 
  • Relationships with business users and technical teams   
  • Delivery of high quality solutions meeting business requirements