Data Analytics and Certification

Best Data Analytics Certifications for 2020

Posted in Data Analytics, Certification
Best Data Analytics Certifications for 2020

Once you’ve decided to be certified for data analytics, it is time to choose one that suits you perfectly. There are several factors to sum in when you’re deciding which data analytics certificate to go for, such as:

  • Career outlook
  • Location and availability
  • Experience
  • Present skillset

Now, there is an overabundance of data analytics certification programs offered on both online and offline modes. In this write-up, we would be solely focusing on the top-rated online certifications.

Data Analytics Certification

Following is our pick of the top 4 data analytics certification programs that an aspirant/professional data analyst can opt for:

1. Cloudera Certified Associate CCA Data Analyst

Platform – Cloudera

The Cloudera Certified Associate or CCA Data Analyst is a data analytics certification offered by Cloudera. The Cloudera Certified Associate CCA Data Analyst certification is meant for:

  • Business intelligence specialists
  • Data analysts
  • Database administrators
  • Developers
  • System architects

Specifically, the CCA Data Analyst certification is designed for brilliant SQL developers looking to stand out among the competition. The Certification for data analytics demands the candidates to have the following skills:

  • Analyze data on the cluster by using QL (Query Language) statements in Impala and Hive
  • Prepare data for queries using the ETL (Extract, Transfer, Load) processes
  • Using DDL (Data Definition Language) statements for altering or creating structures in the metastore for use by Impala and Hive

Based on the candidate’s performance, 8 to 12 problems are given with a unique, large data set and a CDH cluster. The total time awarded is 120 minutes. A technical solution with a high degree of precision must be implemented for every question asked.

Exam Details

Name – CCA Data Analyst
Code – CCA159
Duration – 120 minutes
Language(s) – English
Level – Professional
Passing Percentage – 70%

Prerequisites

  • Basics of Linux command line
  • Some knowledge of SQL

Price – $295
Total Questions – 8 to 12
Type – Performance-based tasks on a Cloudera Enterprise cluster

Syllabus

  • Advantages of the open-source ecosystem of big data tools over traditional RDBMSs
  • Analytic and windowing functions: definition and use
  • Combining datasets using JOIN or UNION
  • Creating and using partitions and various file formats
  • Extending the capabilities of Hive and Impala using:
    • Custom file formats and SerDes
    • External scripts
    • Parameters
  • Optimizing techniques for Hive and Impala queries
  • Processing and analyzing semi-structured and unstructured data
  • Providing SQL access to data using Hive and Impala
  • Syntax and data formats of Hive and Impala
  • Storing and querying complex or nested data structures

You can signup here.

2. Microsoft Certified Solutions Expert MCSE: Data Management and Analytics

Platform – Microsoft

The MCSE: Data Management and Analytics is a prestigious, advanced level data analytics certification. It is apt for an individual with multi-years of expertise in:

  • Building enterprise-scale data solutions
  • Leveraging business intelligence (BI) data
  • SQL administration

A professional with MCSE: Data Management and Analytics certification can work on both on-premise and cloud environments. The most notable aspect of this data analytics certification is that there is a multitude of exams to choose from, depending on your interest and career focus.

Candidates need to complete an MCSA certification in any of the following to be eligible for the MCSE: Data Management and Analytics certification:

  • BI Reporting
  • Data Engineering with Azure
  • Machine Learning
  • SQL 2016 BI Development
  • SQL 2016 Database Administration
  • SQL 2016 Database Development
  • SQL Server 2012/2014

Exam Details

Name – One of the following:

  • Developing Microsoft SQL Server Databases (Exam 70-464)
  • Designing Database Solutions for Microsoft SQL Server (Exam 70-465)
  • Implementing Data Models and Reports with Microsoft SQL Server (Exam 70-466)
  • Designing Business Intelligence Solutions with Microsoft SQL Server (Exam 70-467)
  • Developing SQL Databases (Exam 70-762)
  • Implementing a Data Warehouse using SQL (Exam 70-767)
  • Developing SQL Data Models (Exam 70-768)
  • Implementing Microsoft Azure Cosmos DB Solutions (Exam 70-777)

Duration – 120 minutes

Language(s):

  • Exam 70-464, Exam 70-465, Exam 70-466, Exam 70-467:

Chinese (Simplified), English, French, German, Japanese, Portuguese (Brazil)

  • Exam 70-762, Exam 70-767, Exam 70-768, Exam 70-777:

English
Level – Expert-level
Passing Percentage – 70%

Prerequisites

    • One of the following:
      • MCSA: SQL Server 2012/2014
      • MCSA: SQL 2016 Database Administration
      • MCSA: SQL 2016 Database Development
      • MCSA: SQL 2016 BI Development
      • MCSA: BI Reporting
      • MCSA: Data Engineering with Azure
      • MCSA: Machine Learning

 

  • Several years of experience as a data analyst
  • Good knowledge of SQL

Price – $165
Total Questions – 45 to 55
Type – Single and multi-choice questions

Syllabus

  • Developing Microsoft SQL Server Databases (Exam 70-464):
    • Design database objects
    • Implement database objects
    • Implement programming objects
    • Optimize and troubleshoot queries
  • Designing Database Solutions for Microsoft SQL Server (Exam 70-465):
    • Design a database structure
    • Design a troubleshooting and optimization solution
    • Design database security
    • Design databases and database objects
  • Implementing Data Models and Reports with Microsoft SQL Server (Exam 70-466):
    • Build a report with SQL Server Reporting Services (SSRS)
    • Build a tabular data model
    • Build an analysis services multidimensional database
    • Manage, maintain, and troubleshoot a SQL Server Analysis Services (SSAS) database
  • Designing Business Intelligence Solutions with Microsoft SQL Server (Exam 70-467):
    • Design a reporting solution
    • Design BI data models
    • Design BI infrastructure
    • Design an ETL solution
    • Plan Business intelligence (BI) infrastructure
  • Developing SQL Databases (Exam 70-762):
    • Design and implement database objects
    • Implement programmability objects
    • Manage database concurrency
    • Optimize database objects and SQL infrastructure
  • Implementing a Data Warehouse using SQL (Exam 70-767):
    • Build data quality solutions
    • Design, implement and maintain a data warehouse
    • Extract, transform and load data
  • Developing SQL Data Models (Exam 70-768):
    • Configure and maintain SQL Server Analysis Services (SSAS)
    • Design a multidimensional business intelligence (BI) semantic model
    • Design a tabular BI semantic model
    • Develop queries using Multidimensional Expressions (MDX) and Data Analysis Expressions (DAX)
  • Implementing Microsoft Azure Cosmos DB Solutions (Exam 70-777):
    • Partition and Model Data
    • Perform Integration and Develop Solutions
    • Replicate Data Across the World
    • Tune and Debug Azure Cosmos DB Solutions

You can signup here.

3. Associate Certified Analytics Professional (aCAP)

Platform – Certified Analytics Professional Program

Are you an entry-level analytics professional with little to no experience but comprehensive knowledge and high hopes? Then you must check out the aCAP a.k.a. Associate Certified Analytics Professional designation. An aCAP certification certifies that the candidate is:

  • Having a master’s degree in some form of data analytics, i.e., the theoretical knowledge of data analytics and related technologies
  • Ready to opt for the CAP certification
  • Prepared to start and advance in data analytics

Sponsored by INFORMS, the Associate Certified Analytics Professional is not only vendor and software neutral but also a transferrable credential for novice analytics professionals. Some important things to know about aCAP are:

  • Accessible globally via computer-based testing
  • Must be converted to CAP within 6 years post receiving the certification
  • Renew every three years with professional development units

Other than for the purpose of pursuing CAP, aCAP certification can help you stand apart from your contemporaries, increase your professional credibility, make your resume more impressive, and represent your commitment to learning and earning in data analytics.

The aCAP certification is based on the 7 areas of analytics process:

  • Business Problem Framing
  • Analytics Problem Framing
  • Data
  • Methodology Selection
  • Model Building
  • Deployment
  • Lifecycle Management

Exam Details

Name – Associate Certified Analytics Professional
Code – N/A
Duration – N/A
Language(s) – English
Level – Entry-level
Passing Percentage – 70%

Prerequisites

None

Price – $300 (INFORMS member discount available)
Total Questions – 100
Type – Multiple-choice questions

Syllabus

  • 7 areas of the analytics process
  • Data science
  • Data visualization
  • Pattern recognition
  • Problem definition process
  • Problem-solving

You can signup here.

4. Certified Analytics Professional (CAP)

Platform – Certified Analytics Professional Program

One of the top data analytics certifications is the CAP, a.k.a. Certified Analytics Professional certification. Candidates who are able to pass the rigorous CAP exam stand out among the competition. For earning the CAP certification, one needs to successfully:

  • Meet the eligibility requirements for education and experience
  • Master the art of “soft skills.”
  • Commit to the CAP Code of Ethics
  • Pass the CAP exam

The CAP certification needs to be renewed every three years with professional development units. The data analytics certification has a global reach via computer-based testing.

You need to start with submitting an application for the CAP. It is then reviewed by the panel. You will be able to give the exam only if your application is successfully accepted. CAP is a portable credential based on the practice of analytics professionals.

Exam Details

Name – Certified Analytics Professional
Code – CAP
Duration – 180 minutes
Language(s) – English
Level – Medium-level
Passing Percentage – 70%

Prerequisites

Either a bachelor’s degree with 5 years of professional experience or a master’s degree with 3 years of professional experience

Price – $495 (INFORMS members)
$695 (Others)
$350 (aCAP certified candidates)
Total Questions – 100
Type – Four-option, multiple-choice questions

Syllabus

  • 7 areas of Job Task Analysis (JTA)/7 unique areas of the analytics process
  • BI vs. Data Science
  • Components of data science
  • Data visualization
  • Decomposing analytical problem
  • Five E for CAP exam
  • Knowledge statements
  • Pattern recognition
  • Problem definition process
  • Problem-solving
  • Regression predictive and prescriptive analytics

You can signup here.

That completes our list of the top 4 data analytics certification programs. All of these programs feature preparation guides and sources to make you ready for taking and successfully clearing the exam.

However, you can also prepare for the exams with external learning sources. Here is our pick of the best data analytics courses that will prepare or help you check your preparation for the data analytics certifications:

1. Data Analytics: SQL for newbs, beginners, and marketers

Platform – Udemy

Another suitable data analytics course to help you prepare for a data analytics certification in Data Analytics: SQL for newbs, beginners, and marketers. Solely available in English, the comprehensive course covers data analytics, data science, and big data.

For starting with the course, you need to be able to operate the command line. The 1.5-hour course is divided into 29 lectures to make it easier for learners to go through the course at their own pace and convenience.

Created by Lazy Programmer Inc., the Data Analytics: SQL for newbs, beginners, and marketers course has been taken by over 5.5k students at the time of this write-up. It also flaunts an impressive average rating of 4.2 stars out of 5.

Topics covered

  • Aggregating, grouping, and sorting
  • Basic commands of a relational database
  • Joining tables
  • Modifying a table’s data
  • SQL on Spark
  • Survey of SQL databases

2. Introduction to Data Analytics for Business

Platform – Coursera

The Introduction to Data Analytics for Business course from Coursera cover everything that a data analytics candidate require for preparing business analytics. This data analytics course is a joint effort by Coursera and the University of Colorado Boulder.

In actual, the Introduction to Data Analytics for Business is one of the 5 courses in the Advanced Business Analytics Specialization offered by Coursera. Other than English, the course is also available in Korean.

The 4-week data analytics course requires almost 18 hours to complete and comes with flexible deadlines. Instructor support is available around the clock to help you make the most out of it.

Courses

  • Analytical tools
  • Data and analysis in the real world
  • Data extraction using SQL
  • Real-world analytical organizations

3. Beginner’s Guide to Data & Data Analytics by SF Data School

Platform – Udemy

There are many reasons why the Beginner’s Guide to Data & Data Analytics by SF Data School is a best-seller course at Udemy. This comprehensive data analytics course covers everything data analytics, concepts, terms, processes, roles, and tools.

There aren’t any prerequisites for the 90-minute data analytics course. The entire course is delivered in 9 lectures and features a single article for quick reference. The successful completion of the data analytics course will ensure that a candidate has thoroughly grasped all the fundamentals of data analytics.

Topics covered

  • An introduction to data
  • Classification of data analytics tools
  • Data flashcards
  • Data pipelines
  • Data types, files, and formats
  • Roles and skills of data professionals
  • The data analytics “Tool Triangle.”

4. Advanced Business Analytics Specialization

Platform – Coursera

The Advanced Business Analytics Specialization course from Coursera will help students not only prepare for data analytics certifications but also gain real-world business analytic skills. The course will educate learners on leveraging data to solve complex business problems.

At 7-hour a week, the course requires about 4 months to complete. Other than English, the data analytics course is also available in Arabic and Korean languages. As this is a specialization, you will receive a certificate post-completion.

The Advanced Business Analytics Specialization course also comes with a hands-on capstone project. It helps students put their learning to test with the support from course instructors and fellow students.

Courses

  • Advanced business analytics capstone
  • Business analytics for decision making
  • Communicating business analytics results
  • Introduction to data analytics for business
  • Predictive modeling and analytics

Conclusion

Gaining certification in data analytics will help you stand higher than the competition. However, remember that certification solely doesn’t guarantee you a successful and satisfying career. You also need to have relevant experience and an attitude to learn and improve continuously.

Want to refine further and improve your data analytics skills? Try these top-rated data analytics courses recommended by the Hackr community.

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Simran Kaur Arora

Simran Kaur Arora

Simran works at Hackr as a technical writer. The graduate in MS Computer Science from the well known CS hub, aka Silicon Valley, is also an editor of the website. She enjoys writing about any tech topic, including programming, algorithms, cloud, data science, and AI. Traveling, sketching, and gardening are the hobbies that interest her. View all posts by the Author

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Minnie Stevens
Minnie Stevens

Who uses data analytics?

Drew Newman
Drew Newman

Big data analytics involves examining large amounts of data. Organizations have realized the growing need of evolving from a knowing organization to a learning organization. Essentially, businesses want to be more objective and data-driven, and so they are embracing the power of data and technology, more than ever. Big data analytics have helped organizations and businesses harness their data and use it to identify new opportunities. That, in turn, results in smarter business moves, more efficient operations, higher profits and happier customers. From banking, to health care, life sciences, manufacturing, retail, government, every sector is now into data analytics.

Roberta Bryan
Roberta Bryan

What is required to learn data analytics?

Darrel Hill
Darrel Hill

Love for numbers and quantitative stuff, structured thinking approach, willingness to learn statistical concepts, creative and analytical thinking and a passion for solving problems, are some of the skills and aptitudes required if you wish to be a data analyst. Talking about technical requirements, a bachelor’s degree in a field with an emphasis on statistical and analytical skills, such as math or computer science, is a pre-requisite. Data analysts should be proficient in one language, such as R and SAS for data gathering, data cleaning, statistical analysis, and data visualization, and have working knowledge of a few more. In-depth knowledge of at least one of these analytical tools, for data science R is generally preferred.

Terry Goodwin
Terry Goodwin

What are data analytics tools?

Candice Barton
Candice Barton

Given the growing demand and importance of data analytics in the market, there are a huge number of tools that have made an entry. The open source tools are more popular, user-friendly and performance oriented than the paid ones. These tools and software help in finding current market trends, customer preferences, and other information widely used for meaningful analysis of a large set of data. Excel, SaS, QlikView, BI Tools, Tableau, are some of the tools widely used by data analytics.

Chelsea Parks
Chelsea Parks

What are the basics of data analytics?

Isabel Wood
Isabel Wood

For you to work in data mining and business intelligence firms, understanding of fundamentals of data analytics is very important. Data analysis is all about numbers and statistics. A data analyst’s main role is to structure, analyze and interpret raw data, using machine learning models, or algorithms, and statistics, in order to solve business problems, or find patterns or trends, etc. they play a vital role in helping companies understand their customer needs and track increasing profits.

Vickie Wise
Vickie Wise

Does data analytics require coding?

Diana Clark
Diana Clark

Data analysts don’t need to have advanced coding skills, but have experience with analytics software, data visualization software, and data management programs. While coding is not required; good understanding of ML algorithms, strong programming and analytical skills, statistics are some areas that are key and required when you become a data scientist. Learning to code or a program language can surely help gain a competitive edge in the field.

Wanda Carroll
Wanda Carroll

Is Data Analytics a good career?

Seth Wagner
Seth Wagner

Data analytics deals with systematic study of big data to achieve business goals. Skilled data analysts are considered as some of the most sought-after professionals in the world. It is a well-paid job since the demand is high but such professionals are less in number. Some of the top jobs in data analysis involve using data to make investment decisions, target customers, assess risks, or decide on capital allocations.