How IBM uses Big Data
Big Data:
Big Data describes the large volume of data in a structured and unstructured manner. The data belongs to a different organization and each organization uses such data for different purposes. So a large amount of data is not critical, the rather critical part is how organizations are using this data.
Big Data is a data set that is huge and complex so that traditional data processing applications are inadequate to deal with them. There are challenges to managing such a huge volume of data such as capture, store, data analysis, data transfer, data sharing, etc. Big Data follows the 3V model as “High Volume”, “High Velocity” and “High Variety”.
Characteristics of Big Data:
The term “big data” refers to data that is so large, fast or complex that it’s difficult or impossible to process using traditional methods. The act of accessing and storing large amounts of information for analytics has been around a long time. But the concept of big data gained momentum in the early 2000s when industry analyst Doug Laney articulated the now-mainstream definition of big data as the three V’s:
Volume: Organizations collect data from a variety of sources, including business transactions, smart (IoT) devices, industrial equipment, videos, social media and more. In the past, storing it would have been a problem – but cheaper storage on platforms like data lakes and Hadoop have eased the burden.
Velocity: With the growth in the Internet of Things, data streams in to businesses at an unprecedented speed and must be handled in a timely manner. RFID tags, sensors and smart meters are driving the need to deal with these torrents of data in near-real time.
Variety: Data comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, emails, videos, audios, stock ticker data and financial transactions.
Why Is Big Data Important?
The importance of big data doesn’t revolve around how much data you have, but what you do with it. You can take data from any source and analyze it to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimized offerings, and 4) smart decision making. When you combine big data with high-powered analytics, you can accomplish business-related tasks such as:
- Determining root causes of failures, issues and defects in near-real time.
- Generating coupons at the point of sale based on the customer’s buying habits.
- Recalculating entire risk portfolios in minutes.
- Detecting fraudulent behavior before it affects your organization.
Who is using Big Data?
The people who’re using Big Data know better that, what is Big Data. Let’s look at some such industries:
1) Healthcare
Big Data has already started to create a huge difference in the healthcare sector. With the help of predictive analytics, medical professionals and HCPs are now able to provide personalized healthcare services to individual patients. Apart from that, fitness wearables, telemedicine, remote monitoring – all powered by Big Data and AI – are helping change lives for the better.
2) Academia
Big Data is also helping enhance education today. Education is no more limited to the physical bounds of the classroom – there are numerous online educational courses to learn from. Academic institutions are investing in digital courses powered by Big Data technologies to aid the all-round development of budding learners.
3) Banking
The banking sector relies on Big Data for fraud detection. Big Data tools can efficiently detect fraudulent acts in real-time such as misuse of credit/debit cards, archival of inspection tracks, faulty alteration in customer stats, etc.
4) Manufacturing
According to TCS Global Trend Study, the most significant benefit of Big Data in manufacturing is improving the supply strategies and product quality. In the manufacturing sector, Big data helps create a transparent infrastructure, thereby, predicting uncertainties and incompetencies that can affect the business adversely.
5) IT
One of the largest users of Big Data, IT companies around the world are using Big Data to optimize their functioning, enhance employee productivity, and minimize risks in business operations. By combining Big Data technologies with ML and AI, the IT sector is continually powering innovation to find solutions even for the most complex of problems
6. Retail
Big Data has changed the way of working in traditional brick and mortar retail stores. Over the years, retailers have collected vast amounts of data from local demographic surveys, POS scanners, RFID, customer loyalty cards, store inventory, and so on. Now, they’ve started to leverage this data to create personalized customer experiences, boost sales, increase revenue, and deliver outstanding customer service.
Retailers are even using smart sensors and Wi-Fi to track the movement of customers, the most frequented aisles, for how long customers linger in the aisles, among other things. They also gather social media data to understand what customers are saying about their brand, their services, and tweak their product design and marketing strategies accordingly.
7. Transportation
Big Data Analytics holds immense value for the transportation industry. In countries across the world, both private and government-run transportation companies use Big Data technologies to optimize route planning, control traffic, manage road congestion, and improve services. Additionally, transportation services even use Big Data to revenue management, drive technological innovation, enhance logistics, and of course, to gain the upper hand in the market.
Big Data Case Study
IBM
International Business Machine (IBM) is an American company headquartered in New York. IBM is listed at # 43 in Forbes list with a Market Capitalization of $162.4 billion as of May 2017. The company’s operation is spread across 170 countries and the largest employer with around 414,400 employees.
IBM has a sale of around $79.9 billion and a profit of $11.9 billion. In 2017, IBM holds most patents generated by the business for 24 consecutive years.
IBM is the biggest vendor for Big Data-related products and services. IBM Big Data solutions provide features such as store data, manage data and analyze data.
There are numerous sources from where this data comes and accessible to all users, Business Analysts, Data Scientist, etc. DB2, Informix, and InfoSphere are popular database platforms by IBM which supports Big Data Analytics. There are also famous analytics applications by IBM such as Cognos and SPSS.
IBM’s Big Data Solutions are as below:
#1) Hadoop System: It is a storage platform that stores structured and unstructured data. It is designed to process a large volume of data to gain business insights.
#2) Stream Computing: Stream Computing enables organizations to perform in-motion analytics including the Internet of Things, real-time data processing, and analytics
#3) Federated discovery and Navigation: Federated discovery and navigation software help organizations to analyze and access information across the enterprise. IBM provides below listed Big Data products which will help to capture, analyze, and manage any structured and unstructured data.
#4) IBM? BigInsights? for Apache? Hadoop?: It enables organizations to analyze a huge volume of data quickly and in a simple manner.
#5) IBM BigInsights on Cloud: It provides Hadoop as a service through the IBM SoftLayer cloud infrastructure.
#6) IBM Streams: For critical Internet of Things applications, it helps organizations to capture and analyze data in motion.