Press "Enter" to skip to content

Big Data Challenges (How You Can Solve Them Easily)

Sandeep Mittal 0

Big Data Challenges

No company can feature without data those days. With large quantities of data being generated each 2nd from enterprise transactions, income figures, buyer logs, and stakeholders, Big Data Challenges is the gas that drives companies. All these data receives piled up in a large data set this is cited as Big Data.

This data desires to be analyzed to enhance choice making. But, there are some demanding situations of Big Data encountered via way of means of companies. These encompass data quality, storage, loss of data technology professionals, validating data, and collecting data from unique sources.

We will take a more in-depth examine those challenges and the methods to conquer them.

Challenges of Big Data

Many agencies get caught on the preliminary level of their Big Data projects. This is due to the fact they may be neither privy to the challenges of Big Data nor are ready to address the one’s challenges.

Let us read one by one –

1. Lack of proper understanding of Big Data

Companies fail in their Big Data projects because of inadequate understanding. Employees might not understand what data is, its storage, processing, significance, and sources. Data experts can also additionally recognize what goes on, however, others might not have a clean picture.

For example, if personnel does now no longer recognize the significance of data storage, they may not hold the backup of touchy data. They may not use databases nicely for storage. As a result, while this vital data is required, it can’t be retrieved easily.

Solution

Big Data workshops and seminars ought to be held at organizations for everyone. Basic education programs ought to be organized for all of the personnel who’re managing data frequently and are part of the Big Data projects. Primary information of data standards ought to be inculcated with the aid of using all tiers of the organization.

2. Data growth issues

One of the maximum pressing challenges of Big Data is storing most of these big sets of data properly. The quantity of data being saved in data facilities and databases of agencies is growing rapidly. As those data units develop exponentially with time, it receives extraordinarily tough to handle.

Most of the data is unstructured and is derived from documents, videos, audio, textual content documents, and different sources. This way which you can’t locate them in databases.

Solution

In order to address those huge data sets, corporations are choosing cutting-edge techniques, such as compression, tiering, and deduplication. Compression is used for decreasing the wide variety of bits withinside the data, for that reason decreasing its typical length. Deduplication is the technique of getting rid of replica and undesirable data from a data set.

Data tiering lets businesses to save data in unique storage stages. It guarantees that the data is living withinside the maximum suitable garage space. Data stages may be a public cloud, non-public cloud, and flash storage, relying on the data length and importance.

Companies also are choosing Big Data tools, such as Hadoop, NoSQL, and different technologies.

3. Confusion while Big Data tool selection

Companies regularly get confused even as choosing the nice device for Big Data evaluation and storage. Is HBase or Cassandra the nice technology for data storage? Is Hadoop MapReduce exact sufficient or will Spark be a higher alternative for data analytics and storage?

These questions trouble organizations and from time to time they’re not able to discover the answers. They turn out to be making bad selections and choosing a beside the point era. As a result, money, time, efforts, and paintings hours are wasted.

Solution

The excellent manner to head about its miles to is seeking for expert help. You can both lease skilled experts who understand a great deal greater approximately those tools. Another manner is to head for Big Data consulting. Here, experts will supply advice on excellent tools, primarily based totally on your company’s scenario. Based on their advice, you may train session a method after which pick out the excellent tool for you.

4. Lack of data professionals

To run that modern technology and Big Data equipment, businesses want professional facts experts. These experts will consist of data scientists, data analysts, and data engineers who’re skilled in operating with the equipment and making feel out of big data sets.

Companies face the trouble of loss of Big Data specialists. This is due to the fact data dealing with gear have developed rapidly, however, in maximum cases, the experts have not. Actionable steps want to be taken so one can bridge this gap.

Solution

Companies are making an investment extra money withinside the recruitment of professional experts. They additionally need to provide schooling applications to the present workforce to get the maximum out of them.

Another essential step taken via the way of means of agencies is the acquisition of data analytics answers which can be powered via way of means of artificial intelligence/machine learning. These gear may be run via way of means of experts who aren’t data technological know-how specialists however have simple knowledge. This step allows corporations to store plenty of cash for recruitment.

5. Securing data

Securing those big units of data is one of the daunting demanding situations of Big Data. Often businesses are so busy in understanding, storing, and reading their data units that they push data protection for later stages. But, this isn’t a clever circulate as unprotected data repositories can turn out to be breeding grounds for malicious hackers.

Solution

Companies are recruiting extra cybersecurity experts to guard their data. Other steps taken for securing information include:

  • Data encryption
  • Data segregation
  • Identity and get entry to control
  • Implementation of endpoint protection
  • Real-time protection monitoring
  • Use Big Data protection tools, such as IBM Guardian

6. Integrating data from a variety of sources

Data in a company comes from a lot of sources, which include social media pages, ERP applications, client logs, economic reviews, e-mails, shows, and reviews created through employees. Combining all this data to put together reviews is a hard task.

This is a place frequently disregarded by firms. But, data integration is important for analysis, reporting, and enterprise intelligence, so it needs to be perfect.

Solution

Companies ought to resolve their data integration issues by shopping for the proper gear. Some of the excellent data integration equipment are stated below:

  • Talend Data Integration
  • Centerprise Data Integrator
  • ArcESB
  • IBM InfoSphere
  • Xplenty
  • Informatica PowerCenter
  • CloverDX
  • Microsoft SQL
  • QlikView
  • Oracle Data Service Integrator

In order to place Big Data to excellent use, agencies ought to begin doing matters differently. This approach hiring higher staff, converting the management, reviewing current enterprise guidelines, and the technology being used. To decorate selection making, they are able to rent a Chief Data Officer – a step this is taken through the various fortune 500 agencies.

Summary

Lack of proper understanding of Big Data Companies fails in their Big Data projects because of inadequate understanding. Data experts can also additionally recognize what goes on, however, others might not have a clear picture. Big Data Challenges No company can feature without data those days. Another manner is to head for Big Data consulting. Challenges of Big Data Many agencies get caught on the preliminary level of their Big Data projects. Is HBase or Cassandra the nice technology for data storage?

Data growth issues One of the maximum pressing challenges of Big Data is storing most of these big sets of data properly. Solution Big Data workshops and seminars ought to be held at organizations for everyone. Securing data Securing those big units of data is one of the daunting demanding situations of Big Data. All these data receive piled up in a large data set this is cited as Big Data. Confusion while Big Data tool selection Companies regularly get confused even as choosing the nice device for Big Data evaluation and storage.

Leave a Reply

Your email address will not be published.