Challenges,Big,data,Business,I marketing Challenges of Big data Business Intelligence
Automation technologies represent a fundamental aspect of any modern industry. The major types of industrial automation solutions, such as DCS, PLC, SCADA, and MES, are used on a large-scale in process and discrete industries.DCS technologie Awhile ago, I got an email from one of the "gurus" I follow and it shocked me. The gist of it was this person wanted to trade services for a household item.To say it floored me would be an understatement.What was worse was a few days later t
Business Intelligence or dashboard reporting or Enterprise Performance Management tools have been around from a long time and have reached a level of maturity with the advent of big data. Big data means velocity, volume and variety. These things became very important thanks to the evolving social media. Internet, online advertising and digital companies depend on Business Intelligence to derive insights into their business using vast amount of data they deal with everyday. The objective of using these tools is to analyze huge amounts of data and generate intelligence that can improve business performance. Take advantage of these solutions is of significant importance as they provide visibility into trends, risks and opportunities for improvement. But, Big data BI poses a few challenges to these companies:Infrastructure Investment: When compared to typical Line of Business applications for daily operations this is phenomenal. It includes storage, bandwidth, and servers, skilled resources like data scientists and statisticians and data transfer costs. Investment also varies on the amount of data stored and processed. Streaming & Real Time Analytics and Insights are vital but involve significant infrastructure framework and additional investment.So, organizations need to look at hidden costs and assess the situation accurately before taking investment decisions.Too many options: Software assessment and evaluation is time consuming. There are too many private big data Business Intelligence tools and software applications. These choices create significant confusions and make organizations battle to decide which software to implement.Complexity: Traditional Business Intelligence solutions need to extract data from different and often distinct sources. Even though the new breeds of Data Discovery tools, which are a segment of Business Intelligence, accelerate the procedure, it still demands significant labor and time to sort them out and analyze. Once it is analyzed it often requires extensive effort to generate insights. The level of effort required to produce meaningful intelligence from data may even exceed the cost of finding and sorting it.Unstructured data: Most of the data available today is unstructured. It is the data generated from videos, word documents, Pdfs, PowerPoint presentations, comments and likes in social networking sites. It is a challenging task to extract, align and manage unstructured data in a stable and timely manner. Organizations should use next generation technologies like machine learning to sort out this data and derive intelligence from it.A well-established Business Intelligence solution is of great value and requires a significant effort. It is a challenge to derive information, which can drive action that can change the way an organization, is performing, which is one of the reasons many organizations fail to deploy an effective Business Intelligence solution. Article Tags: Data Business Intelligence, Data Business, Business Intelligence
Challenges,Big,data,Business,I