Proactive implementation of big data improves the bottom line
Big data describes the large volume of data which includes both structured data (such as numeric values, currency, alphabetic, name and date) types and unstructured data (such as audio, video and photos) types. The volume of data is growing based on day-to-day business operations and it is important for an organization to use the data for better decision-making and devising strategies.
Big data mainstream is based on 3Vs:
Volume: Data is collected from various sources such as business transaction, social media, RFID tags and smart devices.
Velocity: Unprecedented speed of data streams must be dealt with in a timely manner. For example, sensors and smart metering drive large volume of data in real time.
Variety: Data comes in various formats such as email, video, audio, stock ticker and financial transaction.
This article explores big data technology which has the potential to change business operations and gain competitive advantage through data-driven strategy. It also helps in understanding big data market scenario, its market dynamics, best practices for big data implementation and how this may help in operational cost saving.
Why big data?
Research shows that companies which are data-driven have outperformed their competitors by about 20 percent. It is estimated that mainstream adoption of big data analytics may increase the output of global retail and manufacturing industries by $325 billion by 2018.
Big data market is expected to grow at a CAGR of 26 percent from 2014 to 2018 and is estimated to reach $42 billion by 2018. North America has the leading market share in big data technology with about 56 percent of global market share. Research shows that during FY 2014-2015, 75 percent of companies were investing or planning to invest in big data in the next two to three years.
Increasing adoption of big data technology
There was about 60 percent increase in big data adoption between 2013 and 2014. Prevailing factors for significant increase in big data adoption are: discovery of new business insights through data analysis and gaining of competitive advantage through real time analysis and decision making.
Big data-value chain
With exponential growth of data, companies must be proactive in applying most of the available data to various technologies. They should select key data for specific investigations and integrate large dataset to support specific queries and analysis.
All the actions from data collection to data analysis flow from a data value chain which is a framework to manage comprehensive data from capturing to decision making and to support a variety of business units and their technologies.
Best practices - big data implementation
Suppliers offering big data implementation
Tier1 players providing big data solution are: Tableau, Qlik, Microsoft, MicroStrategy, SAS, SAP, IBM, Oracle and Tibco Software.
Tier2 players providing big data solution are: Birst, Information Builders, Alteryx and Logi Analytics.
Tier3 players providing big data solution are: Prognoz, Pentaho, GoodData, Targit, etc.
- With exponential growth in data across industries, which is forecasted to reach 40 Zettabyte (1 Zettabyte=One million petabytes) by 2020, enterprises across all industry verticals are adopting big data to gain competitive advantage
- Research shows that data driven companies are three times more likely to report significant improvement in decision making and about 80 percent enterprises are in the early stages of big data adoption
- About 59 percent enterprises use customer generated data to gain better visibility on customer’s requirement and plan accordingly for new product/services for better market penetration
- Research shows that big data helps in increasing company’s revenue by about 25 percent within 2-3 years of its implementation
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