Big Data Analytics: a Management Perspective
In today's world data is becoming the new raw material of more and more business processes. Data powers many things we do. To feed this process, businesses collect and store more and more information.
WHAT IS BIG DATA? MEANING
To understand Big Data Analytics, let's first define "Big Data". Big Data is simply an extremely large data set (collection of data) that can be analyzed by using advanced techniques to reveal patterns, traits, etc., which can then be used for decision making. Big data has some characteristics such as "high velocity" - indicating the speed of data generation, "high variety" - indicating the number of data types the Big Data contains, "high volume" - indicating the total amount of data which is present in the information asset.
WHAT IS BIG DATA ANALYTICS? MEANING
Big Data Analytics is the process of using advanced analytical tools and techniques to analyze a large amount of data in order to find hidden patterns and new associations of variables and other insights. It helps marketers, researchers, analysts and other business people to make (more advanced) use of their already existing data and find new opportunities for their business. If you do this really well, it may lead to some level of competitive advantage, since better decisions can be made from relevant data in a reliable way.
Machine learning, predictive analysis, data mining, etc. and other similar advanced techniques can be used on the data to explore opportunities that were unknown.
ADVANTAGES OF BIG DATA ANALYTICS
- New products and business opportunities: For example, if customer needs are properly gauged and that data is properly analyzed then companies can present what the customer actually needs and even create new products and thus satisfy the customers in a better way while increasing revenue.
- Cost Reduction: Big data technologies such as cloud-based analytics and Hadoop can bring significant cost reduction when it comes to large amounts of data. Many SaaS (Software as a Service) companies are making it possible for medium scale enterprises to reduce cost as data storage becomes more convenient using SaaS.
- Faster and better decision making: With advanced techniques which give real-time results, it's very convenient for the marketers to bring in new promotions or new campaigns really fast and thus please the customers. Businesses are able to analyze the information immediately and make decisions.
APPLICATIONS OF BIG DATA IN A MANAGEMENT CONTEXT
- Fraud Detection: For businesses which provide certain types of transaction processing (for example Apple or Google Pay), fraud detection is one of the best applications of Big Data. Years ago, a fraud was detected long after the fraud was committed. Whereas big data platforms with real-time data analysis can detect most kinds of frauds in real-time by analyzing patterns. Any large change in the pattern will create suspicion, thus making fraud detection faster, easier and cheaper.
- Social Media Analysis: Analysis of social media activity is another important application of customer-facing Big Data application. Social media can provide real-time insights into how the market is responding to certain campaigns and products. From these insights, companies can make decisions regarding their promotions and pricing and ad placements for further campaigns.
⇨ Please share your ideas and experiences with Data Analytics to improve this topic. Thanks...
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Gandhi Heryanto
Management Consultant, Indonesia
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The Gap Between Organizational Competence and the Power of Big Data for Decision Making I refer to the paper of Alexander and Lyytinen. They show that organizations are ignoring organizational competencies necessary to marry big data 'evidence' with organizational sense-making and decision-making to generate impactful managerial action. They see a tendency of organizations to overplay the power of big data and its software for the advantages as you describe.
This study examines how organizations can address these challenges and change their organizations by building competencies that enable success with big data. From their survey, it is suggested that organizations can mobilize analytic competencies, continuous learning and experimentation on successful analytic results. Companies must focus on developing analytic skills to design and conduct experiments that are rooted in contextual data to extract business insights that can lead to business processes and product innovation. This study underscores the need to bridge data science and decision science to experiment with data towards better business decisions.
Source: Alexander, D.T. and Lyytinen, K. (2017), "Organizing Successfully for Big Data to Transform Organizations", Americas Conference on Information Systems.
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Jaap de Jonge
Editor, Netherlands
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The Issue of Big Data is not Technology But Organizational Competence @Gandhi Heryanto: Thanks and agreed. The conclusions of Alexander and Lyytinen sound very familiar to me being involved for over 30 years with the use of IT by organizations. I can still recall the days that many organizations started buying and implementing financial administration software (later to be followed by logistics software), but didn't spend enough time, effort and money on training their people on how to actually use it and on how to customize the software to the specific needs of their business. Since then, every time I hear IT vendors screaming: "technology, technology, technology!", I think: "educate, educate, educate!" Developing a big data organizational competence is a nice challenge for middle managers in companies that can benefit from applying big data into their operational decision-making.
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