Data Technologies

Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. The term was coined in the mid 1990s, and the scope of the problem was popularized by IBM’s Blue data projection in 2000 The term “Big Data” has become popular, but there is no consensus on what “Big Data” means. The term is often used to describe data sets that are so large that traditional on-disk data-processing techniques are inadequate.

Big Datasets can only be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. The term “Big Data” was coined by John Mashey in 1987. Big Data your new digital frontier. The volume, velocity and variety of Digital Data are growing at an exponential rate, which could be a challenge for businesses to handle. This data explosion is creating the opportunity for businesses to capture new value by finding new ways to harness all that data.

In fact, the McKinsey Global Institute has estimated that the potential value of big data could be between $250 billion and $500 billion annually. The data could come from any source: sensors, mobile devices, social media, video, CRM systems, voice (just to name a few sources).

Artificial intelligence is a field of computer science that emphasizes the creation of intelligent machines that work and react like humans. These machines are capable of learning from past experiences and adapting to new situations, which is why AI is often used in predictive analytics. Predictive analytics is the process of using computer-based models to forecast future trends and make predictions about future outcomes. It is used in many fields, including healthcare, marketing, finance, manufacturing and more.

The most common way to do this is through artificial intelligence (AI) software algorithms. These algorithms can scan large amounts of data in a speedy manner and extract the most relevant information.

Good news for you as business leader: Augmented analytics. You as a business leader will be able to make better and faster business decisions based on enormous and complex data pipelines.

Augmented analytics is a term that refers to the use of enabling technologies that provide the data and analysis into data analytics and business intelligence platforms. These enabling technologies, such as machine learning and artificial intelligence, enable data to be explored and analyzed without having to use data analytics and business intelligence platforms.

Enter the citizen data scientist. A citizen data scientist is a person who creates or generates models that leverage predictive or prescriptive analytics. This person is not a data scientist but rather an individual who has interest and knowledge in the field of data science. Gartner predicts that 85% of all large and medium companies have at least one citizen data scientist on staff as we speak.