Modern Data Ecosystem, Role and Process of Data Analysis - Nerd Platoon Modern Data Ecosystem, Role and Process of Data Analysis - Nerd Platoon

Businesses today understand that data’s potential value and data analytics play a key role in their ability to compete. Companies are recruiting and upgrading personnel to support their data and analytics projects. In order to establish a multifaceted data and analytics practice in their enterprises, they are growing their teams and establishing centers of excellence.

To quote a Forrester consulting report on the power of data to transform business: “Businesses today understand that data’s potential value and data analytics play a key role in their ability to compete. Companies are recruiting and upgrading personnel to support their data and analytics projects. In order to establish a multifaceted data and analytics practice in their enterprises, they are growing their teams and establishing centers of excellence.” In addition to this, there is a substantial supply and demand imbalance for talented data analysts, making it a highly sought-after and well-paid job. You can decide to specialise in data analytics as a career path or use it as a stepping stone to enter other data-related fields like data science, data engineering, business analytics, and business intelligence analytics.

A modern data ecosystem includes a network of interconnected and continually evolving entities that includes: 

  •         Data that is available in a host of different formats, structure, and sources.
  •         The enterprise data environment, where raw data is prepared for organization, cleaning, and optimization for end-user use.
  •         End-users such as business stakeholders, analysts, and programmers who consume data for various purposes.

Emerging technologies are constantly transforming the data ecosystem and the opportunities it presents, including Cloud Computing, Machine Learning, and Big Data. In the ecosystem for extracting insights and business outcomes from data, data engineers, data analysts, data scientists, business analysts, and business intelligence analysts all play crucial roles.

Data engineer

Data engineers create and manage data architectures and make data accessible for operational and analytical use in businesses. Data engineers harvest, integrate, and organize data from many sources as part of the data ecosystem. Data repositories should be designed, cleaned, transformed, and prepared for storage. They made it possible for data to be accessible in formats and systems that can be used by different business applications as well as stakeholders like data scientists and analysts. A data engineer needs to be well-versed in programming, have a firm awareness of systems and technological architectures, and have a comprehensive knowledge of both relational databases and non-relational data stores.

Data analyst

Data analysts examine and clean data to derive insights, detect correlations and patterns, apply statistical tools to analyze and collect data, and visualize data to understand and communicate the results of data analysis. Data analysts do this so that organizations may make decisions. Analysts are the ones who can respond to queries like, “Are users’ search experiences on our site generally positive or negative?” or How do people generally feel about our rebranding initiatives? Or do sales of one product and another relate to one another? Spreadsheets, writing queries, and utilizing statistical tools to build charts and dashboards are all skills that data analysts need to be proficient in. Today’s data analysts also need to be able to program. They also need strong analytical and storytelling skills. 

Data scientists

Data scientists are key players in data echo-systems that examine data to uncover insights that may be put to use and develop machine learning or deep learning models that learn from historical data to produce predictive models. What proportion of my clients am I likely to lose to competitors in the upcoming quarter? How many new social media followers am I expected to gain next month? Are these financial transactions uncommon for this customer? are just a few of the queries that data scientists can respond to. Data scientists need to have a basic understanding of programming, databases, and developing data models in addition to math and statistics skills. Additionally, they require domain expertise.

Business analysts and BI analysts

Data scientists and analysts’ work is used by business analysts to assess prospective effects on their company and suggest or implement the necessary actions. They focus on the market dynamics and other elements that affect how their business is shaped. They provide business intelligence solutions by gathering, tracking, and analyzing data on numerous business processes to produce insights and useful information that improves corporate performance.

Now, lets talk about the process that involves data analysis process.

  •         Developing an understanding of the problem and the desired outcome. 
  •         Setting a clear metric for evaluating outcomes. 
  •         Gathering, cleaning, analyzing, and mining data to interpret results.
  •         Communicating the findings in ways that impact decision-making.