By 2025, it is predicted that the value of data will increase by 10-fold. Virtually, every branch of industry or business will generate vast amount of data. Thus, the world will experience an aggressive growth and data could be a missed opportunity when not being utilized. And to make matter worse, the rate of collecting and storing data is faster than the ability to use them as a tangible decision-making. With the help of ever-growing technology, visionaries are creating visualization methods to help turning raw data with no value to an informative data. Big data has served a purpose for organizations to optimize their businesses. With an abundant amount of data that organization generate every day, the ability to turn the data into a decision, effectively and efficiently is crucial. Thus, the knowledge of analytics and visualization would come hand-in-hand to tackle the problem in big data. Hence, a new Continue reading
Data Management
What Is Data Strategy?
Data Strategy defines a set of choices and actions that, together, define a high-level course of action to achieve high-level goals. It involves business plans to use knowledge to a competitive advantage to support business objectives. A Data Strategy requires an understanding of the data needs inherent in the Business Strategy. Like many other terms, “data strategy” has several synonyms in data management. They include but are not limited to business data strategy, business data management strategy, information management strategy, business information management strategy, information strategic plan. All these terms refer to the same concept of a single, enterprise plan for the use of organizational data as an essential asset for strategic and operational decision-making. A data strategy defines the approach that the enterprise will take to manage and use its data and information to achieve its business and technology goals and to realize a competitive advantage using this asset. The Continue reading
Why is Big Data so Important in Today’s World?
In the ever-changing, globalized economy, companies have started depending on assessments advanced by their internal processes, business operations, and customers to explore new opportunities for advancement and growth. Such insights present a massive intricate set of data that are produced then managed, analyzed, as well as manipulated by experts. The collation of such a large amount of data is collectively referred to as big data. The numerous peta and terabytes are presently considered as the big data benchmark. The main characteristics which describe big data include; volume which refers to the amount of produced and stored data that determines the potential and the value of the insight and if it can truly be assumed as big data or not. Secondly, the variety referring to the nature and type of the data to assist the data analyst to successfully use the subsequent insights; Velocity refers to the speed that determines how Continue reading
Data Analytics in Healthcare Industry
Health is the most integral part of life. In the healthcare industry a vast amount of data is generated from different segments of healthcare organizations such as hospitals, healthcare service providers, insurance providers etc. However, like other sectors ranging from retail to banking, who have already leveraged the potentials of big data, the healthcare industry has not yet fully explored the importance of big data in deriving valuable insights from such vast amount of data at hand. For example, Grocery stores determine the loyalty of their customers by identifying the sales patterns, giving discounts and special offers, having a mix of products which not only improve their profits but also, increases their customer satisfaction. Claims providers and payers, the pharmaceutical industry has now only utilized big data to tackle issues such as changes in the quality of healthcare services, reducing fraud and abuse of claims, improved care. Due to the Continue reading
Data Analytics in Retail Industry
Data acquisition using the Internet of Things (IoT) in the retail industry is one of the most important innovations in increasing the amount of relevant data that can be collected during a customer’s visit. Analyzing the behavior of a customer during an in-store purchase using sensing devices can reveal a customer’s interests and choices. Using a number of sensing devices, the in-store customer behavior is captured, pre-processed, and then transmitted over a wireless network to the cloud. A data analytics model built with fuzzy logic is developed to generate the data of a customer’s purchasing intentions. This approach will help retail stores to recommend products to customers and guide supply chain planning. Such an approach allows retailers to gain more sales thereby increasing their market value. The increase in the amount of data available due to the advent of automation, new technologies, and standards have made the decision-making process in Continue reading
Uses and Risks of Personal Data in Big Corporations
Big Data has taken a huge role in art in creating today’s Technological Revolution. It is a phrase coined to describe the exponential volume of data we currently hold. Data is collected from a number of sources including cell phones, applications, databases, servers, etc. In return, it can then be used to find trends, patterns, and connections specifically related to how humans behave along with their interactions. This information includes likes, dislikes, preferences, and search and buyer history and is not limited to personal data such as birthdate, social security number, home address, and much more. Corporations across the globe have found new ways to use this data in everyday business functions. The collection of Big Data can be used to a company’s advantage in marketing, finance, and Government. Despite the fact that in a few situations Big Data can be hard to control, it can possibly enable organizations to Continue reading