Data Analytics: From excel to Big Data

Data can be any information in a form that is efficient for movement or processing like numbers, words, images, video, or sound. Data can be of great value to a business, however, this value is not obvious but must emerge through its proper analysis and presentation.  

More and more companies today collect and analyze large volumes of data and for this reason, the traditional way of analyzing with excel is no longer sufficient.

The solution suggested is to use modern tools such as those offered through Data Analytics that comes to facilitate the analysis of big data. But before we go into that let's answer some basic questions:
 

  1. How is data analysis done today?

    Data analysis till today in some cases is still done using Excel. Excel for several years has been the first choice in general data management from storing, organizing, analyzing to presenting the results through simple charts of various types. Nowadays the use of excel is considered so trivial that nobody mentions its use as an additional skill or gets a certificate of use as we did in the early 90's. The use of excel has some limits in terms of the possibility of analysis so in this case, we have to look for other tools that can make our work more efficient.
  2. Why is it no longer sufficient to use Excel?

    As the volume and complexity of data increases, so does the need to use new means of analysis beyond excel or other simple statistical tools. The new analytical tools developed in recent years have been created in response to new technological challenges and in order to meet the ever-increasing needs. The use of the internet (1989) and its increasing speed (5G, 2019), the development of social media (2004), and the way we can exchange data (cloud) have created the need for easy and fast analysis of a lot of data and this is not possible with traditional tools.
     
  3. What is Data Analytics?

    Data Analytics is a set of techniques we use to analyze raw data to find trends and answer questions. Data Analytics is part of a more general set described by the term Data Science.

    Data analytics focuses more on looking at historical data in context, while data science focuses more on machine learning and predictive modeling. Data science is a multi-dimensional mix that includes algorithm development, inference from data, and predictive modeling to solve analytically complex business problems. On the other hand, data analytics encompasses a few different disciplines of broader statistics and analytics.


     
  4. What is the demand for data analytics in the market?

    The Data Analyst profession has been booming in recent years and good Data Analysts are in demand. Usually this job direction is followed by professionals from various disciplines, for example, finance, accounting, business administration or science. A Data Analyst should be familiar with Datawarehouse, Databases (sql & nosql), Python and Open Source reporting or Visualization tools (PowerBI / Tableau).
     
  5. How to be an expert in Data Analytics?

    Upskilling εspecially in tech is absolutely important!
    Are you still wondering how you can be Data Analyst?
    Big Blue Data Academy in collaboration with Deree - The American College of Greece offers the Professional Diploma in Data Analytics programThis Professional Diploma is designed for undergraduates, graduates (Bachelor, Master, or Ph.D.), and professionals aiming to enhance their knowledge and skills to pursue careers as Data Analysts, Business Intelligence Analysts, and Data Officers.

By Sophia Verouti