Complete Data Analytics Certification Guide & tutorials

What is Data Analytics?

What is Data Analytics? Definition with Examples - projectcubicle
Data analytics

Data analytics allows organizations to examine all their data of real-time, historical, unstructured, structured, qualitative to detect patterns and produce perception to inform and, in some cases, automate decisions, connecting intelligence and action.

It also enables organizations to digitally transform their business and culture, turning out to be more inventive and forward-thinking in their decision-making.

Going beyond traditional KPI monitoring and reporting to searching concealed patterns in data, algorithm-driven organizations are the new pioneers and business leaders.

Data analytics is a wide term that incorporates many different types of data analysis.

Types of Data Analytics

  • Predictive data analytics
  • Prescriptive data analytics
  • Diagnostic data analytics
  • Descriptive data analytics
  • Cognitive analytics
What is Data Analytics - Understanding Big Data Analytics
Types of Data analytics

Three key aspects of modern data analysis

  • Augmented analytics
  • Data visualization, reports and dashboards
  • Embedded analytics

What is the use of Data Analytics?

Here is the list of top 5 use cases of Data Analytics –

  • Security Intelligence – Data analytics are also place for enhancing security options against hackers and cybercriminals. An IT division handles a lot of data. Security is a significant concern; many organizations presently utilize these analytics to help in acquiring improved solutions to detect and stop such attacks. User and Entity Behaviour Analytics, Security Information and Event Management (SIEM) tools, and Machine learning can be utilized to recognize anomalies and strange user activities.
  • Customer Relationship Analytics – One of the difficult tasks in marketing is to recognize clients who will burn through cash reliably for a long time. This business knowledge will assist the organizations with acquiring such clients which will be a lifetime value for the organization. The Data analytics in business incorporate Telecommunications, Banking, utilities, and retail. Customer division additionally helps in laying out potential marketing strategies.
  • Recommendation Engines – You might have been noticed “recommendations for you” on YouTube, Spotify, or other media services. These customized recommendations are efficient and help in further developing the general user experience. This can be a winning component as there is a lot of competition in the entertainment and media sector. Even, you could also see some recommendations during shopping online.
  • E Commerce – A system-wide infrastructure with data analytics is a better way than upgrade the effectiveness and execution of the business. The system metrics are utilized to trace the performance of IT modules and the user logs. These will figure out user behavior in e-commerce sites. By utilizing this data, retailers can acquire perception that help in creating agile techniques, better business performance, and benefits.
  • Internet of Things – There are vast approaches to applying data analytics to IoT solutions. For instance, almost all industry uutilizes sensor data to have noteworthy experiences as a proportion of preventive support. A customer movement might be followed as a piece of the security choice of a device. Another instance could be logistic tracking, where the vehicles are traced from time to time and diverted in the case of terrible weather, or unanticipated conditions that influence the delivery time. These analytics work based on real-time IoT information and can track down better routes for safe, fast, and economical delivery.

Compare Data Science Vs data analytics Certification

DifferencesData ScienceData Analytics
ScopeMacro (Superset)Micro (Sub-set of Data Science)
TargetAsking the right questions, device data-driven solutionsSearching functional insights, produce business reports
Uses Big DataYes, oftenYes, sometimes
Unstructured DataYes, oftenMostly not
Statistical AnalysisAdvanced KnowledgeBasic to Intermediate
AI & Machine LearningYesNo
Programming ToolsIntermediate to AdvancedNone to Basic
What is data analytics - scope, careers, and skills required

List of Data Analytics Certification

  • DevOpsSchool certified Data analytics professional
  • Microsoft Certified: Data Analyst Associate
  • Google Data Analytics Certificate
  • Cloudera Certified Associate Data Analyst
  • Associate Certified Analytics Professional
  • Springboard Data Analytics Certification
  • AWS Certified Data Analytics

Data Analytics Certification Path

These are the path from where you can get data analytics certified –

  • Microsoft-Data Analyst Associate [Exam DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI (beta)]
  • Cloudera-Certified Associate Data Analyst
  • DevOpsSchool-Mater in Data Analytics
  • Amazon-AWS Certified Data Analytics – Specialty

Data Analytics Certification Cost

  • Microsoft**-Data Analyst Associate – $165 USD*
  • Cloudera-Certified Associate Data Analyst (CCA Data Analyst Exam (CCA159) ) – 3195.00 USD
  • DevOpsSchool-Mater in Data AnalyticsRs 49,999
  • AWS Certified Data Analytics – 300 USD

Best salary for Data Analytics Certified Professional

The average salary of Data Analyst salary in India is ₹325,616, mid-level Data Analyst salary in India is ₹635,379, experienced Data Analyst salary in India is ₹852,516.

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Rajesh Kumar
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