We live in exciting times, where tasks and gadgets that were recently considered science fiction have become an exciting reality. Technology is moving at an accelerated pace, and data is everywhere. As such, that data must be collected, interpreted, encrypted, protected, and more. The field of data analytics has risen to fill this growing need, and it continues to grow. In … [Read more...] about What Will Data Analytics Look Like in 2020?
Big Data
Learn everything you need to know about big data. Find out how companies are using this revolutionary technology and what it means for your business strategy.
How is Technology Keeping Our Financial Data Safe?
Business intelligence (BI) is a term used to define the tools and methods to create summaries and actionable steps for an organization's business decision making. Linking big data and tools like artificial intelligence, BI collects and processes large volumes of data to provide a snapshot of the current state of the organization's financial and operational status, and those of … [Read more...] about How is Technology Keeping Our Financial Data Safe?
The Birth of Big Data on Cloud Infrastructure and its use in Business Decisions
Big data - alongside sustainability, the Internet of Things and crypto - is arguably the buzzword of the decade. It's a term that describes the large volume of data that inundates a business on a day-to-day basis - and represents the potential means to an end for businesses with respect to some of the most complex and burdensome organisational procedures. But having big data … [Read more...] about The Birth of Big Data on Cloud Infrastructure and its use in Business Decisions
How High-Tech Is Fostering More Innovation Districts
Years ago, people would drive miles for jobs in secluded office buildings to keep ideas and technology a secret. Today, technology has changed how and where individuals work. The high-tech field, such as big data, machine learning and AI, requires collaboration, which is why innovation districts are becoming popular options. What Are Innovation Districts? An innovation district … [Read more...] about How High-Tech Is Fostering More Innovation Districts
5 Ways AI and Big Data Are Changing the Customer Experience
AI-driven technologies (e.g., natural language processing and machine learning) are now used in many customer service applications to help brands deliver an outstanding customer experience that will drive sales and increase customer retention. In fact, 78% of contact center professionals believe that AI will have a positive impact on call center applications and 77% are … [Read more...] about 5 Ways AI and Big Data Are Changing the Customer Experience
What is big data?
Big data is a term that refers to the massive amount of digital data created and shared every day. Big data can transform how we live, work, and communicate. It can be used to improve everything from public health and urban planning to business and marketing.
Big data is also changing the way we think about privacy and security. The volume, velocity, and variety of big data present challenges and opportunities for organizations and individuals. Regardless, big data is here to stay, and its impact will only continue to grow in the years to come.
What is big data analytics?
Big data analytics is the process of turning large, complex data sets into actionable insights. Businesses use various analytical tools and techniques, including machine learning and statistical analysis, to do this.
Big data analytics can be used to improve decision-making in areas like marketing, operations, and customer service. It can also be used to identify new business opportunities and optimize existing processes. With the help of big data analysis, businesses can gain a competitive edge by using their data better.
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When was big data introduced?
The term big data was coined in the 1990s, with some giving credit to John Mashey for popularizing the term. However, the concept of big data has been around for much longer.
Where does big data come from?
In the early days of computing, scientists and businesses began to realize that the amount of data being generated was increasing exponentially. As a result, they began to develop new methods for storing and processing data.
Over time, these methods have become increasingly sophisticated and have played a key role in enabling businesses to make sense of vast amounts of information. Today, big data is used in various industries, from retail to healthcare, and its importance is only likely to grow in the years to come.
What are examples of big data?
One of the most common examples of big data is social media data. With over 2 billion active users, Facebook generates a huge amount of data every day. This includes information on user interactions, posts, and even location data. Analyzing this data can help companies better understand their customers and target their marketing efforts.
Another example of big data is GPS signals. These signals are constantly being generated by devices like cell phones and fitness trackers. When combined with other data sets, GPS signals can be used to provide insights into everything from traffic patterns to human behavior. Finally, weather patterns are another type of big data set. By tracking these patterns over time, scientists can better understand the impact of climate change and develop strategies for mitigating its effects.
How do companies use big data?
Companies use big data in marketing, product development, and customer service. By analyzing large data sets, businesses can identify patterns and trends that would be otherwise difficult to spot. For example, a company might use big data to track customer behavior patterns to improve its marketing efforts.
Alternatively, a company might use big data to improve its products by identifying areas where customers are most likely to experience problems. For instance, big data can be used to improve customer service by finding pain points in the customer journey. Ultimately, big data provides companies with a valuable tool for gaining insights into their business operations.