What is Big Data?

Big Data describes the collection and analysis of structured and unstructured data to discover social trends, consumer patterns and correlating variables. Big Data is so massively complex that traditional data management tools cannot properly store it or efficiently process it. Keep reading to learn the properties, frameworks, benefits, and challenges of Big Data.

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Big Data Properties

Big Data has four common properties or attributes. First, Big Data has high volume because it contains online and offline data from cellphones, computers, machines, networks, social media, and digital human interactions. Second, these data types and sources offer a diverse variety because they include things like photos, emails, videos, social media posts, and search engine queries. Third, it offers value because it analyzes how data is used in making different decisions and exploring the world. This provides new information uses, insights and opportunities. Fourth, Big Data velocity refers to the fast flow of continuous streaming information.

Big Data Tools

Forbes magazine states that there are 2.5 quintillion bytes of data created every day. This averages to 912 quintillion bytes of data every year. Specific software solutions and platforms must be used to access Big Data insights. Apache Hadoop is a popular framework that uses a storage system called Hadoop Distributed File System (HDFS) to provide high availability of data clusters. Microsoft HDInsight is a cloud-based, Apache Hadoop solutions that uses Windows Azure Blob as the basic file system. NoSQL is a Java-based software to handle structured data. It’s noted for offering better performance for storing huge amounts of data. Other solutions include Hive, Sqoop, and PolyBase.

Big Data Benefits

Big Data offers many proven benefits to organizations. It reduces the costs of operations, production, and service delivery by identifying problems and anticipating solutions. A hospital chain may use it to lower re-admissions, optimize treatments and track high-cost patients. A logistical shipping company may use it to reduce adverse problems and analyze supply chain costs. All of this is accomplished through predictive modeling that empowers preemptive risk management and smarter financial decisions. Pharmaceutical companies use Big Data to reduce the costs of research and development by predicting which medication trial patients will most likely comply with and finish studies.

Big Data Challenges

Big Data comes with a hefty price tag because of the expense and difficulty in connecting different software systems to data warehouses. Software interfaces may need to be developed to integrate systems and extract data from a wide variety of sources in different formats. Thus, there is a lack of data connectivity and standardization. The labor challenge continues because there is a lack of trained IT, analytical and data scientist professionals with the right experience. Similarly, new technology leadership is needed to recognize and take advantage of Big Data benefits and opportunities. Finally, quality assurance is needed to ensure that predictive models are not based on flawed data analytics.

Organizations who ignore or miss Big Data opportunities will not be as successful with innovation, competition, and productivity. Big Data tools and platforms provide useful insights into better efficiency, quality, safety, and cost savings.