Founder & CEO at Datamam, a leading technology company specializing in real-time analytics, discusses the recent shift in data analysis methods towards real-time data analytics. This new approach allows analysts to access and utilize data as soon as it becomes available, changing the way they work and the insights they can uncover. However, the challenge now lies in effectively capturing real-time data and making immediate decisions based on this information.
The foundations of real-time analytics date back to the earliest datasets from Mesopotamia around 4,000 B.C., evolving into modern data analytics by the 19th century with the development of computer hardware technologies. Real-time data analytics have revolutionized data analysis by recognizing the value of fresh data and leveraging it at its peak value. This realization has led to businesses increasingly turning to real-time analytics as a key factor within the business landscape.
Success stories across industries demonstrate the power of real-time data analytics in transforming operations and boosting success. For example, Delta Air Lines invested in real-time flight data to improve baggage handling processes, resulting in a significant reduction in mishandled baggage. Similarly, Netflix utilized subscriber data and real-time analytics to grow into a global streaming company, significantly increasing its revenues over the years. Businesses that embrace real-time data analytics can gain a competitive edge and drive growth in their respective industries.
Internal and external data sources play a crucial role in powering instantaneous insights through real-time data analytics. Internal data is generated within an organization, while external data offers a broader context and identifies new opportunities or challenges. Leveraging external data through tools like web scraping, which retrieves public information from websites in a structured format, is essential for businesses looking to optimize operations and gain competitive advantages. Developing ethical guidelines and selecting the right tools are key steps in starting with data scraping.
The future of decision-making is set to undergo a significant upgrade with the adoption of real-time data analytics and web scraping for external data. Companies that embrace these technologies can gain valuable insights into the immediate effects of their decisions and anticipate future outcomes. While web scraping for external real-time data is still relatively new, companies that invest in this approach are expected to see significant results and advantages in their decision-making processes. This shift towards real-time analytics represents a new era in data analysis and decision-making for businesses across industries.
