11 Oct Improving Efficiency With Big Data
In today’s business environment, which has been impacted by reproducing data, shrinking budgets and rising customer demands, companies that can make the correct decisions at the right time have a competitive advantage. There has been a business paradigm shift over the past several years. It is no longer acceptable for business leaders to only rely on their judgement to make strategic decisions. Today’s business leaders have to be properly equipped with as much information as possible to enable them to make better decisions.
The key to obtaining actionable insights means you need to leverage the huge amounts of data that floods into businesses of all types and sizes. Business analytics provide the insights that help businesses make decisions by utilizing a combination of past data, responding to current needs of a business in real time and predictive modeling to design a roadmap for future growth. The amount of data that flows into businesses has been growing exponentially for years, there is no sign that this trend of growth will slow.
While the management of this amount of data can be a daunting, smart companies are leveraging this data to benefit their businesses. Big data is defined as datasets that are too large to be gathered, stored, managed and analyzed by typical database software tools. This information can generate a wealth of value for businesses of any size and type. Companies that can harness the power of big data can drive both operational efficiency and quality, leading to cost, labor savings and a competitive edge. Leveraging big data can also help companies streamline processes, fighting fraud and reducing errors.
Information technology research and advisory firm, Gartner defines a strategic technology as one with the potential for significant impact on the company in the next three years. Factors that signify significant impact include a high potential for disruption to IT of the business, the need to invest large amounts of cash or the risk of being late to adopt. Big data has been identified as one of the top 10 technologies of 2012, Gartner reports the size, complexity of formats and speed of delivery exceeds the capabilities of traditional data management technologies. It requires the use of new and cutting edge technologies simply to manage the volume and variety of data. Leveraging big data can enable businesses to:
Make large amounts of information available and usable
Drive operational efficiencies and help improve the process, leading to better operating margins.
Collect very large amounts of information to reveal the differences in buying patterns, personal productivity and more.
Acquire the information that will lead to better and more informed management decisions.
Sift through important information that can help determine product and service improvements.
Improve customer segmentation, leading to more tailored marketing efforts and improve cross-sell and upsell success.
Companies that invest in big data need to figure out the value these investments will deliver over a period of time. The value delivered by big data based initiatives should be measured and sustainable over a period of time. While utilizing big data can add value to businesses of all types in many different ways, acquiring the personnel with the skills necessary to perform and use big data analytics to an organization’s advantage will become more and more difficult in the future.
According to research performed by MGI and McKinsey & Company’s Business Technology Office, by 2018 the United States alone could face a shortage of 140,000 to 190,000 people with the deep analytical skills and 1.5 million managers and analysts with required knowledge to use big data analysis for effective decision making. Outsourcing Center and Wipro performed a survey that looked at how organizations are managing and analyzing proliferating data, and determined how firms are leveraging big data for the benefit of their businesses.
While not a comprehensive picture of how these organizations are approaching big data, the survey results identify some general trends in this emerging area. The respondents to the survey were from retail, financial services, transportation/logistics, manufacturing, healthcare, telecommunications and other industries. The volume, variety and complexity of data have grown significantly in the past five years alone, and businesses are facing major data handling challenges.
They look for a cost effective way to store and process all these sources of data and to find a way to develop insights, which provide them with the ability to drive better decision making backed by data. Big data platforms can help organizations meet today’s big data related challenges. Some specific businesses seem to have greater big data challenges than others. However, organizations in all sectors can benefit enormously from a big data strategy.
According to the Outsourcing Center/Wipro research, big data is a challenge for more than half of all the businesses that responded. Wipro’s Jayant Prabhu, principal consultant said, “Data volumes continue to explode with a proliferation of devices, social media tools, video usage and emerging forms of both structured and unstructured data.” What’s more, says Prabhu, the rate of data explosion may be occurring faster than Moore’s Law. Data growth, especially unstructured data growth, poses a special challenge as the volume and diversity of data types outstrip the capabilities of older technologies such as relational databases.
This also provides a great opportunity for organizations to leverage the combination of enterprise data with new age data forms to obtain better quality insights about their customers, operations, etc. In the future, the key challenge with big data will be its size and the fact that normal software and processes can’t handle it well.
There are plenty of challenges that businesses have dealing with big data. First, the sheer size of 100s of Terabytes to Petabytes of data is impressive. Data, much of it semi-structured or unstructured, is coming from sources with very little or no information on it’s scheme. Performing analytics on large datasets requires a different set of skills, technologies and techniques not commonly found in existing business and data analytics teams. This is why it imperative that businesses need a sound strategy for dealing with the overwhelming amount of data that will only continue to grow.
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