Importance of Data Analytics for Businesses – Start Learning now!

The impact of the Fourth Industrial Revolution on the global workforce could lead to the loss of more than five million jobs by 2020 . It has been highlighted that two-thirds of these jobs come from routine office administration and office management positions. The reduction of job positions is also predicted for manufacturing and production sectors. Obviously, urgent steps for re-training and upskilling of employees need to be taken to ensure that people will stay active and successful in the job market under demanding conditions of the technological developments and constant changes and adjustments.

Job market researchers highlight 2 types of job positions which are expected to become critically important to many industries: data analysts and specialized sales representatives. In this post, we discuss the importance of data analytics for businesses and explore opportunities to learn more about the subject and respective skills

Why is data analytics important?

With the help of data analytics, organizations identify new opportunities which lead to smarter business decisions, more efficient operations, and satisfied customers.

The benefits of using data analytics are linked to different areas of company’s performance:

Improved customer services. Data analytics allow businesses to predict customer demands, plan business commitments, and meet customer requirements.

Better organized work with suppliers. Analysis of suppliers’ performance helps decide which suppliers meet company’s requirements, provides best business support, and the order delivery discipline.

Maximizing customer retention. With the help of data analytics applied to customer profiles and activities, businesses can identify customers who are likely to come back to do business. It helps to develop strategies for building long-term relationships with customers and optimize marketing investments.

Cutting down operational costs. Applying data analytics to workforce costs and staffing, companies can improve recruitment strategies and apply a flexible approach to staffing. It allows opening and filling in extra positions during high seasons and keep fewer employees when the business runs slower.

Optimized advertising. Data analytics can be used to assess the content and positioning of all advertisements, product images, and business website pages for their effectiveness and the result.

Improved product management. Data analytics can help understand which products are most popular depending on the specific regions, seasons, age groups, and cultural preferences. It will allow the company to manage deliveries of the required products to targeted customer groups during specific seasons.

Applying data analytics to different operational areas, companies can achieve amazing improvements and make business processes more efficient and effective.

If you are willing to learn more about data analytics tools and gain the skills, click the link below and join courses offered by Coursera:
Learn Strategic Business Analytics from ESSEC Business School on Coursera. Enroll today!

Strategic Business Analytics Specialization

Description

This specialization is designed for students, business analysts, and data scientists who intend to apply statistics to business contexts. Specialization requires learners to have some background in statistics, programming skills, and understanding of databases and data analysis techniques such as regression, classification, and clustering.

Courses cover a wide variety of analytics approaches in different industry areas. Learners engage in hands-on case studies which reflect real business situations. Provided examples include predicting and forecasting events, customer segmentation, and calculation of customer scores and lifetime value.

This specialization also teaches how to effectively present analysis results to stakeholders. The third and the fourth courses are designed in partnership with Accenture, one of the world’s best-known consulting and technology services companies. Courses provide information about applications in a wide variety of business sectors, including media, communications, and public services.

On completion of this specialization, learners are able to use statistical techniques to develop business intelligence summary and present it to enable smart and sustainable business decisions. On successful completion of all four courses, learners earn a Specialization Certificate.

Created by: ESSEC Business School in partnership with Accenture

Learning approaches:

  • Online reading material
  • Prerecorded videos
  • Theoretical quizzes
  • Practical quizzes
  • Discussions
  • Peer reviews
  • Reflection

Join the specialization now. Click the link below.
Learn Strategic Business Analytics from ESSEC Business School on Coursera. Enroll today!

Course 1. Foundations of strategic business analytics

Duration: 4 weeks

Rating: 4.4 out of 5

With this course, learners have the initial overview of Strategic Business Analytics topics. Learners discuss a wide variety of Business Analytics applications: Marketing, Supply Chain, Credit Scoring, and HR. The course covers a variety of different data analytics techniques.

The course teaches how to produce convincing, actionable, and efficient insights. The course also presents different data analytics tools which can be applied to different aspects of the business. Learners develop four sets of skills needed to leverage value from data: Analytics, IT, Business and Communication.

By the end of this course, learners are able to approach a business issue using Analytics, qualify the issue, conduct relevant data analysis, and present conclusions and recommendations in an actionable and efficient way.

Course 2. Foundations of marketing analytics

Duration: 5 weeks

Rating: 4.5 out of 5

This course is addressing an important domain – Marketing Analytics which consists of such topics as text mining, social network analysis, sentiment analysis, real-time bidding, online campaign optimization, etc.

Learners will study techniques which will help them to answer the key Marketing questions:

  • Who are the customers?
  • Which customers should be targeted, and
  • What is the future value of customers?

The course covers the following topics: customer segmentation, scoring models, and customer lifetime value. These are the foundations of Marketing Analytics.

Course 3. Case studies in business analytics with ACCENTURE

Duration: 3 weeks

Rating: N/A

This course is a preparation for the capstone project. The objective of the course is to give learners a generic overview of what’s happening in this field. Learners explore how the analytical tools are used in real life projects.

At the end of this course learners will be able to:

  • identify the possible applications of business analytics,
  • reflect on the possible solutions and added-value applications that could be proposed for their capstone project.

The business cases will be presented by senior practitioners from Accenture; they present business cases from different industries and different countries.

The course will prepare learners for the capstone project of the specialization.

Course 4. Capstone: Create Value from Open Data

Duration: 4 weeks

Rating: 3.7 out of 5

The Capstone project is an individual assignment. Learners decide the theme they want to explore and define the issue they want to solve. Their case should provide data from various sectors. Participants are encouraged to mix the different fields and leverage the existing information with other datasets.

The Capstone Project is organized into 3 stages:

  • Deliverable 1 – the preliminary preparation and problem qualification step.
  • Deliverable 2 – learners need to present the intermediary outputs and adjustments to the analysis framework.
  • Deliverable 3 – learners need to present the final outputs and the value case.

Feedback Summary

This specialization has a wide variety of comments which actually reflect the complexity of the courses, and the necessity to have some preliminary knowledge.

Positive feedback

  • Very interesting course.
  • Good lectures & business examples.
  • Good knowledge acquired from the course
  • The course is really practical and presented from the business point of view
  • This course very helpful; it explains how those methods can be implemented in analyzing various business problems for strategic planning.
  • Excellent course and perfectly taught by the professor.
  • The course is easy to understand. With a very basic knowledge of R, one can understand a lot about marketing analytics.
  • The Course provided valuable insights in Strategy
  • Accenture cases were helpful.
  • It has improved presentation skills.

Critical comments

  • Needs real statistic knowledge to understand and see the potential of this course.
  • Simple, methodology is not enough, not practical, more focus on statistical tool data processing instead of insight analysis,
  • Not recommended to professionals.
  • Difficult to understand for a person without software/coding background
  • It is almost impossible to pass because the questions are not organized in a manner of constructive feedback.

Conclusion

Business data analytics is a very important area of ensuring business success and future development in the competitive environment. Having good data analytics skills, it is possible to identify issues, find and action improvements, and forecast business development models.

If you are interested in developing these important skills, click the link below and join the online courses.
Career skills to jumpstart your future.

 

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2 thoughts on “Importance of Data Analytics for Businesses – Start Learning now!”

  1. Data analytics sound really interesting. I’ve always been interested in getting to the root of problems and how to solve them. How long is the duration of this course?

    1. Hello Yvonne,
      Thank you for the comment. Yes, data analytics is number one in the job market. If you are interested to join, please do so… It takes 16 weeks to complete the course. Wishing you all the best,
      Nadja

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