If you're new to access the knowledge of big data then must prefer this previous blog:
"BIG DATA: The Big Mean"
It is already true that Big Data has drawn huge attention from researchers in information sciences, policy and decision makers in governments and enterprises. As the speed of information growth exceeds Moore’s Law at the beginning of this new century, excessive data is making great troubles to human beings. However, there are so much potential and highly useful values hidden in the huge volume of data. A new scientific paradigm is born as data-intensive scientific discovery (DISD), also known as Big Data problems.
A large number of fields and sectors, ranging from economic and business activities to public administration, from national security to scientific researches in many areas, involved with Big Data problems. On the one hand, Big Data is extremely valuable to produce productivity in businesses and evolutionary breakthroughs in scientific disciplines, which give us a lot of opportunities to make great progress in many fields. There is no doubt that future competitions in business productivity and technologies will surely converge into the Big Data explorations. On the other hand, Big Data also arises with many challenges, such as difficulties in data capture, data storage, data analysis, and data visualization.
This blog is aimed to demonstrate a close-up view about Big Data, including Big Data applications, Big Data opportunities, and challenges, as well as the state-of-the-art techniques and technologies we currently adapt to deal with the Big Data problems. We also discuss several underlying methodologies to handle the data deluge, for example, granular computing, cloud computing, bio-inspired computing, and quantum computing.
Well, we'll see some points likewise Big Data's Applications, Skills needed to acquire a job as a Big Data employer, and the jobs which are available in the Big Data Industries.
Let's see which points are necessary to choose Big Data as Career Point of View,
Let's see which points are necessary to choose Big Data as Career Point of View,
The Applications of Giant Big Data Drive Industries:
- Banking And Securities:
A study shows that the challenges in this industry include: securities fraud early warning, tick analytics, card fraud detection, archival of audit trails, enterprise credit risk reporting, trade visibility, customer data transformation, social analytics for trading, IT operations analytics, and IT policy compliance analytics, among others.
In Real World, The Securities Exchange Commission (SEC) is using big data to monitor financial market activity. They are currently using network analytics and natural language processors to catch illegal trading activity in the financial markets.
Retail traders, Big banks, hedge funds and other so-called ‘big boys’ in the financial markets use big data for trade analytics used in high-frequency trading, pre-trade decision-support analytics, sentiment measurement, Predictive Analytics, etc.
This industry also heavily relies on big data for risk analytics including; anti-money laundering, demand enterprise risk management, "Know Your Customer", and fraud mitigation.
- Communications, Media & Entertainment Industry:
Organizations in this industry simultaneously analyze customer data along with behavioral data to create detailed customer profiles that can be used to:
- Create content for different target audiences
- Recommend content on demand
- Measure content performance
Spotify, an on-demand music service, uses Hadoop big data analytics, to collect data from its millions of users worldwide and then uses the analyzed data to give informed music recommendations to individual users.
Amazon Prime, which is driven to provide a great customer experience by offering, video, music, and Kindle books in a one-stop shop also heavily utilize big data.
- Healthcare sector:
Some hospitals are using data collected from a cell phone app, from millions of patients, to allow doctors to use evidence-based medicine as opposed to administering several medical/lab tests to all patients who go to the hospital. A battery of tests can be efficient but they can also be expensive and usually ineffective.
Free public health data and Google Maps have been used by the Universities to create visual data that allows for faster identification and efficient analysis of healthcare information, used in tracking the spread of chronic disease.
Education:
Big data is used quite significantly in higher education.
For example, Some Universities with over a big amount of students has deployed a Learning and Management System that tracks among other things, when a student logs onto the system, how much time is spent on different pages in the system, as well as the overall progress of a student over time.
In a different use case of the use of big data in education, it is also used to measure teacher’s effectiveness to ensure a good experience for both students and teachers. Teacher’s performance can be fine-tuned and measured against student numbers, subject matter, student demographics, student aspirations, behavioral classification, and several other variables.
- Manufacturing & Natural Resources:
In the natural resources industry, big data allows for predictive modeling to support decision making that has been utilized to ingest and integrate large amounts of data from geospatial data, graphical data, text and temporal data. Areas of interest where this has been used include; seismic interpretation and reservoir characterization.
- Government:
In governments, the biggest challenges are the integration and interoperability of big data across different government departments and affiliated organizations.
In public services, big data has a very wide range of applications including energy exploration, financial market analysis, fraud detection, health-related research, and environmental protection.
Some more specific examples are as follows:
Big data is being used in the analysis of large amounts of social disability claims, made to the Social Security Administration (SSA), that arrive in the form of unstructured data. The analytics are used to process medical information rapidly and efficiently for faster decision making and to detect suspicious or fraudulent claims.
The Department of Homeland Security uses big data for several different use cases. Big data is analyzed from different government agencies and is used to protect the country.
- Insurance:
In a survey conducted by Marketforce challenges identified by professionals in the insurance industry include underutilization of data gathered by loss adjusters and a hunger for better insight.
Big data has been used in the industry to provide customer insights for transparent and simpler products, by analyzing and predicting customer behavior through data derived from social media, GPS-enabled devices, and CCTV footage. The big data also allows for better customer retention from insurance companies.
- Retail Trade:
Big data from customer loyalty data, POS, store inventory, local demographics data continues to be gathered by retail and wholesale stores.
Some companies like Microsoft, Cisco and IBM pitched the need for the retail industry to utilize big data for analytics and for other uses including:
- Optimized staffing through data from shopping patterns, local events, and so on
- Reduced fraud
- Timely analysis of inventory
Social media use also has a lot of potential use and continues to be slowly but surely adopted especially by brick and mortar stores. Social media is used for customer prospecting, customer retention, promotion of products, and more.
- Transportation:
In recent times, huge amounts of data from location-based social networks and high-speed data from telecoms have affected travel behavior. In most places, transport demand models are still based on poorly understood new social media structures.
Some applications of big data by governments, private organizations and individuals include:
- Governments use of big data: traffic control, route planning, intelligent transport systems, congestion management (by predicting traffic conditions).
- Private sector use of big data in transport: revenue management, technological enhancements, logistics and for competitive advantage (by consolidating shipments and optimizing freight movement).
- Individual use of big data includes route planning to save on fuel and time, for travel arrangements in tourism, etc.
- Energy & Utilities:
Smart meter readers allow data to be collected almost every 15 minutes as opposed to once a day with the old meter readers. This granular data is being used to analyze consumption of utilities better which allows for improved customer feedback and better control of utilities use.
Must Have Skills to Top Big Data Jobs:
- Apache Hadoop
- Apache Spark
- Data Science & Analytics
- NoSQL Database
- Machine Learning & Data Mining
- Statistical & Quantitative Analysis
- SQL
- Data Visualization
- General Purpose Programming Languages
- Creative and problem solving
If you're really interested in know about what actually skills or demands needed to stay in Big Data Market then this below link will help you to get up to date:
Jobs Available In Big Data:
- Big Data Lead (with DWH Background)
- Big Data Architect (with DWH Background
- Big Data Engineer - R/sas/spss
- Big Data Architect
- Professional Services - Big Data Consultant
- Senior Architect - Engineering Lead - Technology COE - Big Data
- Application Developer: Big Data Biginsights
- Senior Software Engineer - Core Java/ Distributed Messaging/ BigData
- Big Data Engineer - Hadoop/cassandra/mongodb
- Head Data Sciences - Machine Learning/ NLP/ Big Data
- Big Data/hadoop Professionals for a Large IT Service Company
- Specialist - Big Data – Ecommerce
Big Data Jobs in 2018
Conclusion:
Having gone through 10 industry verticals including how big data plays a role in these industries, here are a few key takeaways:
- There is substantial real spending around big data
- To capitalize on big data opportunities, you need to:
- Familiarize yourself with and understand industry-specific challenges
- Understand or know the data characteristics of each industry
- Understand where spending is occurring
- Match market needs with your own capabilities and solutions
- Vertical industry expertise is key to utilizing big data effectively and efficiently. involved