Verdict lists five of the most popular tweets on big data in Q2 2021 based on data from GlobalData’s Influencer Platform.

The top tweets were chosen from influencers as tracked by GlobalData’s Influencer Platform, which is based on a scientific process that works on pre-defined parameters. Influencers are selected after a deep analysis of the influencer’s relevance, network strength, engagement, and leading discussions on new and emerging trends.

The most popular tweets on big data in Q2 2021: Top five

1. KDnuggets’ tweet on the importance of extract transform load (ETL) in data science

KDnuggets, a website focused on artificial intelligence (AI), analytics, big data, data science, and machine learning (ML) founded by data scientist Gregory Piatetsky-Shapiro, shared an article on the importance of ETL in data science. ETL involves the extraction of data from different sources, making changes in the data and loading it into a single destination.

Data is stored in different file formats and in different locations in most organisations, which can be inaccurate and inconsistent making it difficult to gain insights from the data or use it for data science, according to the article. ETL can help in addressing these issues by extracting the data and loading it into a central data warehouse. ETL can also help in running AI and ML applications by providing accurate data for the algorithms.

Username: KDnuggets

Twitter handle: @kdnuggets

Retweets: 60

Likes: 202

2. Kirk Borne’s tweet on the use of data analytics and machine learning to predict stroke

Kirk Borne, chief science officer at DataPrime, a provider of data science, analytics, ML and AI services and products, shared an article on how data analytics and ML can be used for predicting stroke, which is the second largest cause of death in the world. An estimated five billion people in the world get stroke a year, according to the World Health Organization (WHO).

Strokes can be prevented by identifying high risk patients and motivating them to choose a healthy lifestyle. The high-risk patients can be identified using data-science, data analytics and ML, according to the article. Several data analytics and ML models have been applied to evaluate the stroke risk factors including the use of a mixed-effect linear model to forecast the risk of cognitive decline in patients after a stroke. Another model created by researchers accurately predicted stroke outcome with high accuracy, stated the article.

Username: Kirk Borne

Twitter handle: @KirkDBorne

Retweets: 48

Likes: 105

3. Antonio Grasso’s tweet on the key features to look for in big data analytics tools

Antonio Grasso, CEO of Digital Business Innovation, a digital business transformation consulting firm, shared an article on the key features that should be considered when choosing big data analytics tools. The tools should have certain features to meet the user’s needs and improve user experience to achieve successful analytics projects, the article highlighted.

Data breaches and safety issues, for example, can be avoided using big data analytics tools that have well-equipped security features. Some of the important big data analytics features highlighted by the article include data integration, data wrangling and preparation, data exploration, scalability, and data governance.

Username: Antonio Grasso

Twitter handle: @antgrasso

Retweets: 49

Likes: 92

4. Ronald van Loon’s tweet on the role of big data in smart cities and smart vehicles

Ronald van Loon, CEO of Intelligent World, an influencer network that connects companies and experts to new audiences, shared a video on the impact of big data and AI on business practices and developments. He highlighted the role big data plays in the development of smart cars, including research and development, and supply chain management.

Van Loon elaborated on how smart technology is becoming a major part of people’s life in the form of smart homes, smart vehicles and smart cities. Big data can play a key role in integrating smart vehicles with the smart technologies and help in smart city planning and development. He detailed the comments made by Eric Xu, CEO of technology company Huawei, during the Huawei Analyst Summit 2021 on how the company plans to use big data to ensure driving safety in smart cities. Huawei is developing the HI dual-motor electric driving system, which will use AI and big data analysis to alert users of battery exceptions and prevent loss of power during driving.

Username: Ronald Van Loon

Twitter handle: @Ronald_vanLoon

Retweets: 50

Likes: 79

5. Andreas Staub’s tweet on data being the main digital asset

Andreas Staub, head of corporate development and digital transformation at Raiffeisen Switzerland, a retail bank, shared an article on how data is the basis for several other technologies such as AI, cloud computing, and blockchain. Large organisations are becoming data-centric and identifying data as a critical corporate asset.

Most organisations, however, only focus on data-centricity from a disruptive viewpoint rather than understanding its full capabilities. Corporates need to understand the worth of their data and the information contained within and how relevant the data is to the success of their company. Top executives need to ensure that the data is available in a usable format, which will require new approaches that can effectively handle both the volume and types of data.

Data and its various formats need to be tailored in such a way that it can be efficiently used by other technologies such as AI and machine learning. The companies that recognise this will be able to succeed, while laggards will not be able to compete, the article highlighted.

Username: Andreas Staub

Twitter handle: @andi_staub

Retweets: 56

Likes: 55