Companies generate an immense amount of data every day. This data falls into one of two categories – structured data and unstructured data. Structured data is made up of organized and clearly defined data types. An organized data set is easily searchable, and the patterns or trends within it have already been identified for insight. Structured data includes contact information, names, and stock data.
Unstructured data is essentially every type of data that does not fall into that category. Unstructured data is made up of complicated, not easily searchable information. This type of data resides outside of a database management system. A few examples of unstructured data include surveillance data, weather data, and audio. The correlation between each of these data types and big data is that big data refers to all of it collectively.
The term “big data” implies that it may refer to the volume or amount of data. However, big data’s relevancy is not dependent on how much of it you have. The importance of big data stems from its functionality within a relational database and how it can be combined with analytics to improve business intelligence.
Big data usage is highly versatile, but there are a few key aspects that appeal to every business, regardless of their volume of data. These include decision-making processes, cost-effectiveness, and time reduction. Different data types are processed, organized, and shared through data integration platforms across organizations to improve consistency and ease of access.
Data management is especially crucial to businesses that experience regular fluctuations in demand, supply or are heavily influenced by external factors. This need for big data management is partially due to specific business goals such as growth, competitiveness, efficiency, and accuracy. Although, as regulation compliance standards develop, organizations must also find ways to adhere. With a large amount of information comes a large amount of responsibility. Security, integrity, and data privacy are integral motivators for all businesses that have implemented data mining, storage, and analyses techniques.
Strategical data usage can give businesses deeper insight into areas of strength and weakness within their current operational model. The pipeline from data collection to decision-making may seem like a long and arduous process; however, harnessing the power of data can make strategizing simple with the right big data platform. There are three main components of big data analytics: descriptive, predictive, and prescriptive.
Descriptive data refers to parsing a large amount of data to extract essential helpful information like trends or patterns. Predictive analytics then uses the historical data and patterns confirmed by descriptive data to predict possible outcomes of a given scenario. This insight is achieved through the use of mathematical and statistical algorithms that weigh the probability of events. At this stage of the big data management process, prescriptive analytics will come into play. Prescriptive analytics creates actionable insight out of the conclusions drawn from the combination of descriptive and predictive analytics.
The culmination of all these elements of big data management leads to what is referred to as “data-driven culture.” This type of culture is trademarked by trustworthy decisions and actions based on factual evidence. Efficient management of big data eliminates space for errors created by gut-instinct decision-making.
When utilized properly, data can drive all workflow involved in the decision-making process because it can be trusted to operate without biases or personal experiences. Data-driven organizations enjoy higher performance and are at lower risk for security threats, making them more profitable.
For more information regarding big data and data management processes, you may consider visiting TIBCO’s website. TIBCO is the industry leader in data science software. They offer low-cost software licensing perfect for small businesses and college students and host several valuable informational hubs regarding data management and solutions.