In the recent past, some big data thefts have left the world reeling in shock. In one of the most daring incident, a billion yahoo user accounts were hacked. This was at a time when Yahoo Inc. was set to be sold off to Verizon. Although the sale still went through, the devastating news cost the company $350 million off an earlier agreed sale price. Here are the seven big data challenges most companies face.
1. Insufficient Understanding
Many companies have an inadequate understanding of the basics. People do not know what big data is, its benefits and the infrastructure needed. Without this understanding, it is not possible to adopt a big data project successfully. To save your company’s time and resources, check your knowledge on big data. It is imperative that employees understand and are willing to change their existing processes.
Big data marks a huge shift in the way a company runs its affairs. Your top management must first understand the benefits before the rest of the staff is brought on board. The IT department needs to organize enough training and workshops for all the essential players.
2. Various Technologies to Choose From
The market today has a variety of big data technologies. Many companies are confused about what big data technology to choose. In the confusion, a number of them make poor or wrong choices. To make the right choice, you need to have a clear understanding of what you need and what your data requirements are.
In this regard, professional help will save you possible losses and goofs. Hire one or seek the help of a big data professional. With this kind of guidance from industry players and professionals, work out a strategy that works for your company.
Adopting big data projects involves substantial costs. An on-premises solution will cost you in terms of new hardware and staff. You will also need a budget for development, configuration, setup and maintenance of your systems. A cloud-based big data solution, on the other hand, will incur staff costs, cloud service costs, set up and maintenance costs.
Provision for future expansion and scaling up must be factored for both options to lower costs. While the on-premise option is superior in security, although more expensive, the cloud-based option works well for companies without strict security requirements. A more cost-effective way would be to adopt a hybrid solution. This is a mixture of on-premise and cloud-based solutions. In this arrangement, part of the data is stored in the cloud while the more sensitive data is stored on site.
4. Managing Data Quality
Big data involves receiving data from a variety of sources. Most of this data comes in different formats, which immediately raises the issue of data integration. Data from call centres, for instance, and social media, are received in different formats. Integrating these formats into one cohesive database can be quite a challenge.
Besides, due to the unreliability of data obtained from different sources and in various forms, controlling its quality is also not easy. Admittedly, big data is not 100% accurate. A company must invest time and skill to enhance the reliability and consistency of the data. The integrity of the data should, therefore, be at the forefront of your company’s big data policies and strategies.
5. Big Data Security
The bigger the data you are handling, the more the likelihood your company will be targeted by hackers and big data thieves. It is therefore vital to adopt security features and protocols that secure your data behind layers of impenetrable firewalls. As the volume of your data grows, the more you will need to invest in security systems and practices that safeguard your data.
6. Converting Big Data into Profit
Big data should add value to your company. In its raw form, big data is not useful. However, when analyzed and repurposed, it can quickly boost your company’s sales and enhance your brand. The challenge most companies face is that of quickly analyzing data and using it to shore up both their brand and sales.
Data analysis should include looking into your rivals’ data and analyzing it to identify areas where you are strong or weak. To do this, you need to create a reliable system of data sources, which, when analyzed, will yield useful insights that can be acted on to boost competitiveness.
7. Up-scaling Issues
Big data can grow very fast. With this growth comes some enormous challenges. True, you may have thoroughly thought through your big data design, structure and infrastructure. However, the real challenge is in the complexity of scaling it up, which involves a substantial capital outlay.
One of the best approaches to circumventing this problem is by designing a big data solution architecture that includes data algorithms that factor anticipated growth in the future. Your company should monitor system performance to identify weak points and address them as soon as they occur.
How you manage big data is key to the growth of your company. Although it has its fair share of challenges, with proper management, coupled with efficient infrastructure, the benefits of big data far outstrip the underlying challenges.