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Home Tech

8 Big Data Challenges and How to Solve Them

Shivam by Shivam
February 27, 2022
in Tech
Reading Time: 5 mins read
0
Big Data Challenges

Big data has opened new worlds of opportunity for business that span from understanding what consumers want to optimizing organizational processes. In addition, the large volumes of information processed by big data systems have improved accuracy in insights drawn from it. That makes big data crucial in making better business decisions. However, some challenges will make processing this data unfruitful or detrimental to your business. Fortunately, most of them can get remedied to give you a better ROI when investing in this tech.

Table of Contents

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  • 1. Managing data growth
  • 2. Getting high-quality data
  • 3. Data accessibility
  • 4. Skilled workforce
  • 5. Rapidly changing data
  • 6. Technological advancements
  • 7. Compliance Issues
  • 8. Security Issues
  • The bottom line

1. Managing data growth

Recently, there’s been a massive uptrend of data produced by the tech people constantly use in almost every sphere of their lives. This surge of data generated means businesses now have to scale their data management systems to cope with the increased load. In addition, companies now also have to plan for future data growth.

Fortunately, many solutions are available on the market that can help streamline your data systems, like cloud storage and reduced data center costs. In addition, there are many upgrades that you can use to upgrade your system to meet new demands, like the Gigaspaces in-memory computing solution called InsightEdge Smart Cache. Gigaspaces InsightEdge Smart Cache reduces data retrieval latency significantly.

2. Getting high-quality data

A big hurdle with processing big data is collecting and working with inaccurate or low-quality data. Using bad data can be detrimental to your business as your business decisions can only be as good as the intel you get. In addition, bad business decisions can lead to competitors getting an advantage over you or poorer relations between you and your customers.

To ensure the data you get is of high quality, you need to collect it for specific purposes to make it ready to yield tangible results. Several tools are available to collect targeted data like blockchain explorers, which are search engines but can find specific data like individual transactions.

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3. Data accessibility

When all employees who need data or insights can get it on time, more businesses will spot trends sooner. Spotting trends quicker would allow companies to avoid dangers to their business or profit from lurking opportunities.

Unfortunately, most companies usually limit data access to one employee or department. Therefore, businesses must have data approvers who can categorically disseminate data to the relevant people to counter this disconnect. Having data approvers will ensure that only relevant data is used by the different departments and prevent confidential information from getting accessed by everyone in the organization.

4. Skilled workforce

A shortage of skilled workers is a major contributing factor in making it harder for companies to process big data effectively. This lack of skilled workers leads companies to make employees who aren’t adequately qualified to process big data handle it, which usually results in many problems. These problems can be as severe as damage to data or company systems.

To entice skilled workers to apply and stay with their companies, businesses need to constantly improve their brand image to potential employees. Another option is to spot existing employees who show potential and train them for the roles required by the organization.

5. Rapidly changing data

Customers move, lose their phones and change names all the time, and this is just the tip of the iceberg of changes in data that businesses have to address. All these changes in data need businesses to be agile in how they capture their data and how long or frequent they use specific datasets.

To keep up, companies need to review their current data frequently to know when to discard some of it and capture new intel. Additionally, businesses need to check their resources to understand how often or long they can afford to keep or acquire data.

6. Technological advancements

With big data growing in quantity and variety, tech is constantly growing with it. Technology is advancing rapidly, leaving many companies with outdated systems that can’t meet the latest big data demands. Old hardware or software are the leading causes of system crashes and more extended downtimes.

Businesses need to stay updated on the new tech released to prepare in advance for any advancements that might affect how they operate. For example, for software advancements, companies need to keep updating to the latest versions or turn on automatic updates if they can.

7. Compliance Issues

Processing big data rests much responsibility on companies as people’s personal information needs to be handled with care, and there are regulations to ensure it is. In addition, recent data breaches have led governments to penalize billions from companies, emphasizing the importance of knowing the regulations of the countries your data originates from.

Data laws are constantly changing, and to stay compliant, businesses need to ensure that compliance audits are followed at every stage when processing information. That includes checking if your data is collected, stored, and disseminated legally. Allowing customers to decide how they want their data processed can prevent legal trouble too.

8. Security Issues

Businesses live or die through their reputations, and when companies get their security systems breached, consumers don’t want to share their data with them. Sometimes businesses may lose access to a large data pool, sometimes the reputational damage becomes irreparable, and doors end up shut.

To avoid security breaches when handling big data, companies need to do regular vulnerability assessments to determine where they need to increase security. Conducting regular staff awareness campaigns or best practice training can lessen the chances of mistakes that might lead to a breach. Security software also needs to be patched and updated routinely to prevent giving criminals the upper hand.

The bottom line

Big data processing is a worthy investment, but when you choose to use this tech, you need to plan to counter the challenges that will arise. Preparing for these challenges and addressing them in time can save your company money. However, it’s not just company funds that preparation can spare, as your business’ reputation can remain untarnished too. Using the solutions provided here will help you prepare a robust processing system for big data as we’ve covered every aspect from hardware and software to acquiring suitable talent.

Also read: Benefits of IT Staff Augmentation

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Shivam

Shivam

I firmly believed that there should be a hobby that helps you to earn. Thus I made my hobby of writing into my part-time profession and started to write from the last two years. My journey as a writer has enriched me.

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