What is Big Data?
Big Data is a combination of structured, small-scale and informal data collected by non-mining organizations for information and use in machine learning projects, predictive modeling and other advanced mathematical applications.
Six Vs of Big Data
Volume: Can you find the information you are looking for?
Storage capacity is growing faster than ever before, and data that was previously donated to virtual ether is now series of information flowing across the ocean of Big Data. In future, when storage capacity reaches volume beyond belief, it may be possible to capture and record complex data in newer ways, such as sensory perceptions or live events, in real time.
Velocity: Information gains momentum and crises and opportunities evolve in real time. What is the outlook for today?
In an ever-connected world where digital space and virtual space both produce large amounts of data, Big Data is growing bigger and more complex with time. Just as the volume of Internet data took less than a decade to reach double the amount previously collected, the ever-growing amount of data streaming from smartphones and other mobile devices, Internet of Things (IoT), and learning algorithms in advanced equipment, creates a growing knowledge base rich in potential business value.
Variety: Is a picture worth a thousand words in 70 languages? Is your information balanced?
Big Data comes from many sources. In addition to data generating businesses, companies are now able to access new formal, informal, and organized data sources, including:
- Social media forums (e.g. FaceBook posts, tweets, Instagram posts, etc.)
- Sensor data from IoT devices
- Video and audio data from user-created content sites
- Special app data from a variety of sources, such as health records, merchant compliance and performance, eCommerce performance date, etc.
- Feed from commercial and government services
As a result, Big Data figures will only grow in value as we move forward.
Veracity: Are you dealing with Information or misinformation?
The use of Big Data is limited by its accuracy and completeness. Flexible and incorrect data will produce questionable results due to errors. Authentication also applies to "soft" data from social media sites, where consumer behavior analysis measures such as popular sentiments may be hacked or missed even by advanced algorithms. Using Big Data effectively means holding on to reliable data, as well as developing low-level data where possible.
Variability:
Along with its subtlety and complexity, Big Data variability refers to understanding and interpreting the meanings of raw data. As the number of data sources grows and the amount of data taken from each other grows in both volume and complexity, it is important for companies to have a way to streamline data collection, management, and analysis in order to gain and maintain competitive advantage.
Value: AHA to go? Does it convey a message that can be pasted onto a presentation?
Like iron ore or sugarcane, Big Data needs to be refined to be useful. The challenge is to improve the flow of data used to analyze and extract best insights, high efficiency and increase total return on investment (ROI).
Companies use Big Data to improve performance, provide better customer service, conduct personal marketing campaigns and perform other actions that ultimately increase revenue and profitability. The businesses that use it get potential competitive advantage over organizations who do not do so because they are able to make quick and informed business decisions.
Like Facebook and Google, adtech's "duopoly", Amazon has entered the advertising business with the largest amount of consumer data available. Since its inception in 1994, the company has collected information on what most people buy, where the goods are delivered and how credit cards are used. In recent years, Amazon has begun offering more and more companies - including marketing companies - access to its self-help ad site, where they can purchase ad campaigns and target specific demographic statistics, including previous buyers.
Scope:
Today, Big Data influences the IT industry as few technologies have ever done before.
Big Data generated from sensor-enabled machines, mobile devices, cloud computing, social media, satellites help various organizations improve their decisions and take their business to the next level.
It was recently announced that the Office of the Prime Minister of India uses Big Data analytics to understand the feelings and views of an Indian citizen through the website www.mygov.in and social media platforms to access how the common man views government actions.
Google launched the Google Cloud Platform, which allows developers to create a wide range of products from simple websites to sophisticated applications. It allows users to launch virtual machines, store large amounts of data online, and much more. Basically, it will be a single platform for cloud-based apps, online games, mobile apps, etc. All of this required a large amount of data processing as Big Data played a major role in data processing.
Use case # 1: Log statistics
Log data is the basis for many business data applications. Log management and analytics tools existed long before Big Data. But with the growth of business operations and transactions, it can be a major problem to store, process, and deliver log data in the most efficient and most economical way possible.
Many open-source business analytics tools provide the ability to collect, process, and analyze large log data without having to dump the data on the related site and retrieve it with SQL queries. The interaction between log search capabilities and big data analysis has enabled organizations to obtain job information faster. Large data analytics applications are now widely used for a variety of business purposes, from IT system security and network performance to market trends and personalized e-commerce.
Use Case # 2: Customizing E-commerce
Remember when you browse online shopping sites to find that perfect gift for a friend or family member or for yourself? How often do you type in the search box, click the navigation bar, expand product descriptions, or add a product to your cart? If you were an e-commerce company, each of these actions could be the key to mastering every purchase. Therefore, the complex tasks of collecting, processing, and analyzing consumer behavior and purchasing data open huge opportunities for big data in online trading.
Powerful search and large data analysis platforms allows e-commerce companies to-
- refine and enrich product data for better search information on both desktops and mobile devices.
- use predictive statistics and machine learning to predict user preferences with log data, and personalize products in the most affordable way that enhances conversions.
Turning Big Data Challenges into Big Data Opportunities: -
The biggest challenge that comes with Big Data is finding ways to extract quickly and accurately the total amount of data and value. You may not be dealing with an Exabytes of information, but your company may be able to access a lot of random, unfiltered data that you can convert to value in many ways — e.g. cost savings, process improvements, and a healthy foundation, to name just a few.
It is possible to consider the challenges that come with Big Data such as problems and the possibilities of Big Data as opportunities. The game changer would be optimal use of digital technology to support the management and analysis of Big Data.
Challenge: Lack of Awareness, Understanding, and Education
Opportunity: Invest in Needs Analysis, Education and C-Suite Support
Change is as difficult in organizations as it is in individuals — especially, when an organization is large, has a traditional or conservative culture, or has not yet begun to explore digital transformation.
Take the time to honestly evaluate your current data management capabilities, your data needs, and the Big Data volume you use compared to the potential data volume you may mine for useful information. Make it legal and write down your goals for making your experience work and decide how you want to proceed — and the tools you want to use to get to your destination.
By involving the IT department and selecting software tools that provide advanced support and training, it is possible to deliver to the C-Suite quickly and use its support to train the entire team on Big Data technology and ensure that everyone works for the same goals.
Challenge: Plenty of Big Data Requests Available
Opportunity: It starts with the Key Value Processes
The way you choose to manage your data can be as important as the data you want to use. For businesses large and small alike, trying to navigate an endless number of options can be crippling rather than empowering.
One of the most effective ways to start managing Big Data effectively is to improve the procure-to-pay (P2P) process. The P2P process is a good place to start managing large amounts of data because it successfully integrates all spend data and connects to every business process in the organization. Choosing a cloud-based, medium-sized purchasing solution such as PLANERGY provides companies with instant benefits such as full cost transparency, fast and easy access to all participants' mobile phones, and advanced performance tools that make it easy to streamline workflow and analyse data in real time.
In addition to enhancing the P2P process, integrating such a solution allows teams to create a centralized data storage tool for existing software administrators, integrate various data sources to facilitate data cleaning, editing, and analysis — as well as setting up a more advanced digital platform. Change as time, budget, and organizational goals as a whole dictate.
The Cost of initially selecting and integrating cloud-based procurement software solutions can be quickly reimbursed in a number of ways, including but not limited to:
- Improves efficiency, accuracy and speed of all workflows.
- Offloads large, iterative tasks such as approval workflows and data processing to robotic process automation algorithms (“bots”).
- Eliminate fraudulent spending and billing fraud through guided purchases and full spending visibility.
- Increased data-driven insights and greater strategic value by employees who focus their skills on innovation and supplier relationship
- management rather than low-value, boring tasks.
- The benefits of cost savings are important, but they also come with the following “soft savings”: More effective process management to improve
- employee morale, improve supplier relationships, and improve everything from cash flow to contract management.
Choose a modular “future-proof” solution to extend real big data analytics by natively supporting continuous improvement with iterative machine learning. To learn more about Big Data, log onto FutureSkills Prime.
About FutureSkills Prime:FutureSkills Prime started as a platform with a vision to upskill/reskill every Indian citizen in emerging technologies. A joint initiative of Ministry of Electronics and IT (MeitY) and National Association of Software and Services Companies (NASSCOM), it brings a synergy between the Government, Industry, Academia towards the eventual goal of making India a digital talent nation. A novel skilling program, it incentivizes the cost of the eligible course(s), providing authentic and accredited certifications acceptable in the industry.
Written by C-DAC Resource Centre
