What are the Challenges faced by Big Data?

Big Data Uses

Big Data is everywhere and encompasses every industry be it Banking, Technology, Manufacturing or Energy. In the next section, we focus on how each industry uses this barrage of information to their advantage.

Banking

The onslaught of large sets of information pouring in from endless sources has provided the banking sector with an opportunity to innovate new ways to manage and control big data. Banks have to reduce the chances of risk and fraud while continuing mandatory compliance. They have to also make sure that they understand their customers and satisfy their every requirement. With big data, comes great insights, but it also demands that financial enterprises or banks are way ahead of the game with progressive analytical skills.

Big Data challenges faced by the Banking Industry

After going through numerous projects belonging to the top ten investment and retail banks of the world, we can conclude that the most prominent challenges in this industry include the following among many other challenges:

 

  • Early warning for securities fraud
  • Detection of Card fraud
  • Storage of audit data
  • Reprting credit risk of the organization
  • Trade visibility hindrances
  • Transformation of Customer data
  • Trading and its social analytics

Education

Data-driven understanding arms modern-day educators with the tools necessary to make significant alterations in school systems, students and curriculums. We use Big data to analyze and monitor at-risk students, the progress of students, and to enforce an improved system for assessment and aid of teachers and other school employees.

 

Big Data challenges faced by the Education Industry

From a technical perspective, one of the major challenges in this industry is to integrate big data from various starting points and merchants and then use it on programs and platforms incapable of handling the varying data.
Practically and realistically speaking, staffs and institutes have to understand and be thorough with the progressive data management and analysis tools.
From a political point of view, problems revolving around privacy and personal data security of educational institutes is a major roadblock.

Healthcare

Big Data plays a pivotal role in improving patient care all over the world. We need to effectively manage and maintain everything from patient records, treatment plans, to prescription information. At the same time, it must also adhere to all the necessary healthcare industry regulations. In addition to the points mentioned above, we need to streamline the whole process to ensure accuracy and speed.

Big Data challenges faced by the Healthcare Industry

The healthcare sector has passage to enormous amounts of data in their databases. However, we do not utilize this data properly resulting in rising healthcare expenses and inefficient systems. These faulty systems lead to reduced health care benefits and an overall decline in the services provided by this industry. This is primarily due to the fact that there is no available electronic data. The data is either inadequate or unusable.

 

In addition to the above-mentioned problems, healthcare databases that contain health-related information, have made it complicated to integrate data, useful for showing patterns. Patterns are a necessary tool in the medical field and the lack of it is hurting this industry. Other challenges involving Big Data include:

 

  • The elimination of patients from the process of decision making.
  • The proper utilization of data from numerous easily available sensors.

Government

Big data helps governments all across the globe to streamline their activities by empowering them to be more efficient.

 

Big Data challenges faced by Governments

The biggest challenges faced by different Governments today revolve around the integration and interoperability of big data spanning numerous government segments and related organizations.

Given below are a few specific examples:

 

  • We use Big data consistently to analyze large amounts of social disability claims. These claims are made to the Social Security Administration (SSA) and reach in the form of unstructured data. Professionals use analytics to handle medical information swiftly and effectively for agile decision making and to locate dubious or fraudulent claims.
  • The Food and Drug Administration (FDA) is using big data each and every day to expose and research patterns related to food-induced sickness and diseases. This has led to improved treatment times and less number of people dying.
  • The Department of Homeland Security uses big data for numerous additional and different cases. Numerous government departments use and analyze Big data to safeguard the country.

The following names are examples of Big Data Providers in this industry: Digital Reasoning, Socrata, and HP

Natural Resources and Manufacturing

Big Data challenges faced by the Manufacturing and Natural Resources Industry

The world right now is characterized by a boom in demand for natural resources. These include metals, minerals, gas, agricultural products, oil, and much more. Hence, this phenomenon has led to a sharp rise in the volume, complexity, and velocity of data that is a threat to handle. Similarly, humans are not able to tap large volumes of data from the manufacturing industry. The challenge mentioned above prevents the quality, energy efficiency, and reliability to improve, causing reduced profit margins.

 

Applications of big data in manufacturing and natural resources
  • There are a wide variety of uses of Big Data like seismic interpretation and reservoir characterization. In the world of natural resources, Big Data is used for predictive modeling. The large amounts of data (geospatial data, text data, temporal data, and graphical data) are integrated and ingested to support decision making to facilitate better predictive modeling.
  • We use Big data to fix the challenges of today’s manufacturing industry and to achieve a competitive advantage in addition to numerous benefits.

Communications, Media and Entertainment

Big Data challenges faced by the Communications, Media and Entertainment Industry

SThe average consumers always want rich media-on-demand in an array of devices in an assortment of formats. The points mentioned below are some of the big data challenges in this industry:

 

  • How do we collect, analyze, and utilize consumer intuition?
  • Improving social media and mobile content.
  • The patterns of media content usage in real-time

Applications of big data in the Communications, media and entertainment industry

Enterprises in this sector simultaneously analyze behavioral data along with customer data in order to create accurate customer profiles that we can use to:

 

  • What content to create for varying target audiences? Recommending content on demand. How to find out content performance.
  • Wimbledon Championship matches use Big Data to provide us with accurate analysis of tennis matches to mobile, web users, and TV in real-time.
  • Let us take the example of the leading on-demand music service known as Spotify. It collects data from its numerous users worldwide. It then uses this specific data to help users get personalized music recommendations. Spotify needs Hadoop Big Data analytics to perform seamlessly.
  • Amazon Prime, the internet on demand service, heavily uses Big Data. They provide us with a streamlined customer experience. Amazon Prime offers video, music, and Kindle books, all under one digital roof.
  • The following names are examples of Big Data Providers in this industry: Infochimps, Splunk, Pervasive Software, and Visible Measures

Insurance

Big Data challenges faced by the Insurance Industry

The Insurance Industry faces a lot of issues like:

  • The Absence of personalized services
  • The Dearth of personalized pricing
  • The Inadequacy of targeted services to new segments and to specific market segments

 

Marketforce was responsible for conducting a survey in collaboration with Insurance Professionals, which identifies the major challenges in the Insurance Industry. The study concluded that inferior application of gathered data by loss adjusters and the need for better awareness were the two major challenges plaguing this industry.

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How do we apply Big Data in the Insurance Industry?

  • We use Big Data widely in the Insurance Industry for clear and simpler products. This is done by analyzing, and forecasting the behavior of customers through data obtained from CCTV footage, GPS-enabled devices, and social media. The big data also helps in improved customer retention from insurance organizations.
  • We use Big Data extensively for claims management. We use Big Data analytics to analyze a lot of this data in the underwriting stage to make proper forecasts. We can also enhance Fraud Detection.
  • The massive sets of data that we gather from social media and digital channels is used extensively. This helps us to monitor claims in real-time, spanning the entire claim cycle to provide insights.
  • The following names are examples of Big Data Providers in this industry: Sprint, Qualcomm, Octo Telematics, The Climate Corp.

Wholesale Trade and Retail

Big Data challenges faced by the Wholesale Trade and Retail Industry

The world has shifted from traditional brick and mortar retailers and wholesalers to e-commerce traders of the current digital age. In the process a lot of data has accumulated over time. Data is derived from a veriety of sources like customer loyalty cards, RFID, and POS scanners. However, we are not using this derived data to improve customer experiences from any standpoint. The changes made have been slow and ineffective.

How do we apply Big Data in the Wholesale Trade and Retail Industry?

 

    • Retail and wholesale stores are continually gathering data from customer loyalty, local demographics, POS, and store inventory. The Big Show Retail Trade Conference of 2014, held in New York, saw many technology giants like Microsoft, Cisco, and IBM coming together under one roof. They spread awareness about the need for Big Data analytics in the retail trade industry.

 

    • We use Big Data in the retail industry to optimize staffing from shopping sequence, local events, timely analysis of inventory , and reduced fraud.

 

  • There is a lot of potential use for Social media. It is being slowly and steadily adopted by mortar and brick stores. It is used for promotion of products, customer prospecting, and customer retention and much more.

The following names are examples of Big Data Providers in this industry: First Retail, First Insight, Fujitsu, Infor, Epicor and, Vistex.

January 16, 2019
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