What is big data?
Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data.
Big data in action
What types of business problems can a big data platform help you address? There are multiple uses for big data in every industry – from analyzing larger volumes of data than was previously possible to drive more precise answers, to analyzing data in motion to capture opportunities that were previously lost. A big data platform will enable your organization to tackle complex problems that previously could not be solved.
Big data spans three dimensions: Volume, Velocity, Variety.
Volume: Enterprises are awash with ever-growing data of all types, easily amassing terabytes even petabytes of information.
- Turn 12 terabytes of Tweets created each day into improved product sentiment analysis
- Convert 350 billion annual meter readings to better predict power consumption
Velocity: Sometimes 2 minutes is too late. For time-sensitive processes such as catching fraud, big data must be used as it streams into your enterprise in order to maximize its value.
- Scrutinize 5 million trade events created each day to identify potential fraud
- Analyze 500 million daily call detail records in real-time to predict customer churn faster
Variety: Big data is any type of data - structured and unstructured data such as text, sensor data, audio, video, click streams, log files and more. New insights are found when analyzing these data types together.
- Monitor 100’s of live video feeds from surveillance cameras to target points of interest
- Exploit the 80% data growth in images, video and documents to improve customer satisfaction
Big data = Big Return on Investment (ROI)
While there is a lot of buzz about big data in the market, it isn’t hype. Plenty of customers are seeing tangible ROI using IBM solutions to address their big data challenges:
- Healthcare: 20% decrease in patient mortality by analyzing streaming patient data
- Telco: 92% decrease in processing time by analyzing networking and call data
- Utilities: 99% improved accuracy in placing power generation resources by analyzing 2.8 petabytes of untapped data
The 5 game changing big data use cases
What is a use case?
A use case helps you solve a specific business challenge by using patterns or examples of technology solutions. Your use case, customized for your unique issue, provides answers to your business problem.
While much of the big data activity in the market up to now has been experimenting and learning about big data technologies, IBM has been focused on also helping organizations understand what problems big data can address.
We’ve identified the top 5 high value use cases that can be your first step into big data:
Big Data ExplorationFind, visualize, understand all big data to improve decision making. Big data exploration addresses the challenge that every large organization faces: information is stored in many different systems and silos and people need access to that data to do their day-to-day work and make important decisions.
Enhanced 360º View of the CustomerExtend existing customer views by incorporating additional internal and external information sources. Gain a full understanding of customers—what makes them tick, why they buy, how they prefer to shop, why they switch, what they’ll buy next, and what factors lead them to recommend a company to others.
Security/Intelligence ExtensionLower risk, detect fraud and monitor cyber security in real time. Augment and enhance cyber security and intelligence analysis platforms with big data technologies to process and analyze new types (e.g. social media, emails, sensors, Telco) and sources of under-leveraged data to significantly improve intelligence, security and law enforcement insight
Operations AnalysisAnalyze a variety of machine and operational data for improved business results. The abundance and growth of machine data, which can include anything from IT machines to sensors and meters and GPS devices requires complex analysis and correlation across different types of data sets. By using big data for operations analysis, organizations can gain real-time visibility into operations, customer experience, transactions and behavior.
Data Warehouse AugmentationIntegrate big data and data warehouse capabilities to increase operational efficiency. Optimize your data warehouse to enable new types of analysis. Use big data technologies to set up a staging area or landing zone for your new data before determining what data should be moved to the data warehouse. Offload infrequently accessed or aged data from warehouse and application databases using information integration software and tools.