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7 Complex Big data challenges and How to Overcome Them

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The exponential growth of data has forced data scientists to find new ways to capture, share, store, and present data. This has also given rise to new domains such as Big Data Analytics and Data Sciences. To give you a little perspective on how much data we are creating, here is a stat. We create 2.5 billion bytes of data every day. Yes, you read that right.

Managing such a huge amount of data is a challenge, but it pales in comparison when you compare it with a daunting task of extracting actionable insights from this huge set of data. Then there are issues of data validity and authenticity. If you are a data-driven business or organization who relies heavily on data to make decisions, these challenges can hamper your business progress. Despite all these challenges, many businesses are jumping on the big data bandwagon.

Big Data
Big Data

In this article, you will learn about seven big data challenges that are impacting your business and how you can overcome them.

Handling Data Volume

The pace at which the volume of data is growing is mind-boggling. According to the IDC report, the amount of data stored on computers doubles every two years. What’s worse is most of that data is unstructured, which means that it is not organized and stored in multiple formats such as audio, video, photo, docomeents to name just a few.

To solve this problem, businesses are looking at hyper-converged systems that consolidate the storage from a wide range of sources at one place and harnessing the power of the cloud and software-defined storage. Businesses can make the most of technologies such as compression, storage tiers and minimize duplication to reduce the space required to store data. You can also buy dedicated server or more storage if your data needs are high.

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Data Validation

When you are receiving data from multiple sources, it is important to check its validity before using it as a baseline for any future decisions or performing any operation on it. You might come across contradictory data. For instance, your ERP software might be giving you a different sales number while your E-commerce system might paint a different picture.

In such a scenario, it is important to ensure synchronization between data. For that, you will have to use data governance. Govern data by using a combination of technology and implement policies that ensure your data stays in sync. Define rules and procedures and dedicate a team to oversee the implementation of these data governance rules.

Extract Actionable Insights Quickly

There is no point in storing huge amount of data if you are not going to extract meaningful information out of it. Implementing data-driven culture, driving innovation, and accelerating new developments becomes a daunting challenge, especially with most businesses focusing on cutting costs with big data projects.

With the advent of advanced analytical tools, businesses can make sense out of huge data sets, extract valuable insights, and make the right decisions. These powerful analytical tools can deliver real-time results and sift through huge sets of data in no time. One big advantage of these tools is that you can respond to ever-changing market conditions faster and more efficiently.

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Integrating Data Sources

Data is stored on multiple devices, platforms, and sources. Integrating multiple data sources is also a big challenge. Even if you succeed in integrating all the sources of data, ensuring harmony is tough. To resolve this issue and help businesses integrate data sources more seamlessly, many vendors have started offering integration tools, which make the integration process a breeze. Businesses who don’t use these integration tools still find it tough to integrate multiple data sources.

Data Security

When you are storing huge amount of data, some of which might be of a sensitive nature, you are also responsible for safeguarding it from misuse. You also attract attention from hackers as they might consider a software target. Security has always been a major issue for businesses storing big data. A study conducted by IDG revealed that only 39% of companies use additional security measures for their data repositories. Businesses are betting big on access and role-based controls, encryption, and data segregation.

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Finding The Right Talent

In order to handle big data smartly, businesses need data scientists and professionals with big data skills. That is why the demand for big data specialist has grown tremendously in the last couple of years. Companies are ready to pay top dollar to hire the best talent in the industry. If you are still not sure which career path to choose, become a data scientist, and acquire big data skills.

To cover up the huge talent gap in the big data industry, companies are investing heavily in training their existing employees and doing everything they can to retain existing employees, so they don’t have to hire new ones. Other companies are pinning their hopes on self-service analytical tools and seeing it as an alternative to hiring big data professionals.

Resistance to Change

Business alignment, poor understanding of managers, and resistance from employees are three of the biggest issues that you might encounter on the road to implementing a new system. Change management is one of the big challenges of modern day enterprises. You might have to face some resistance, criticism, and face the backlash when you try to implement a new system in an organization. To ensure everything works according to the plan, businesses are hiring chief data officer to monitor the implementation. Both the top management and employees need to understand the real benefits big data has to offer, so they are ready to face and overcome all the hurdles that come in their way. The key to successful implementation is to keep all the stakeholders on the same page.

Which is the biggest big data challenge you have ever faced? Feel free to share it with us in the comments section below.

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