Big Data Challenges And Solutions

Data today flows in torrents and if businesses can make use of even a fraction of this data it would help them advance. However, big data presents challenges that may appear insurmountable. If there are challenges to big data and its utilization by business to derive predictive capabilities, then there are solutions too. Let us take a look at the most common big data challenges and their possible solutions. 

Insufficient Awareness Of The Possibilities Of Big Data 

Enterprises are managed by people with managerial skills and IT takes a backseat. Managers are content with traditional methods of analytics and business intelligence based on data warehouses. They simply are not sufficiently informed as to how much big data can benefit them by widening the scope and bringing in predictive capabilities. The solution is obvious: top management needs to lead the way and seriously focus on how to leverage big data. It pays for the top management to learn and also initiate programs for everyone down in the hierarchy to get a good grasp on the fundamentals of big data and how useful it is for their organization. A good starting point would be to engage a big data development company to act as their consultant and show them how they benefit now and in the future. 

Volume And Complexity

Assuming that enterprises are aware of all the positive benefits that big data analytics can bring, the sheer volume and complexity seem a wall too high to climb. Data flows from a variety of sources and in varieties of types. Apart from the usual company generated data, there is data from external sources such as IoT devices, searches and social media to name only a few. The diversity in sources also creates a diversity of data types. Data is not just text these days. It also covers audio, video and graphics as well as images. What makes it even more complex is that data is unstructured. Data is there for the taking but making sense of it means streamlining data into a structure that analytics software can understand. The solution is to use Hadoop MapReduce or Cassandra or HBase. All these tools are complex and need the services of trained professionals. The shortcut solution is to retain specialists offering custom big data application development solutions. 

Stupendous Infrastructure And High Cost

Whichever way one looks at it, big data adoption is expensive. One must have superior IT hardware infrastructure and that alone is expensive. Then, it needs power, space and people to manage big data. You could be looking at a team of data scientists and analysts who do not come cheap. You need custom big data solution and this also represents significant costs. Businesses can opt for an on-premise solution at tremendous costs or opt for cloud-based solutions at a slightly lower cost. Costs may be driven down by use of data lakes for data that does not need immediate analysis. The solution to bypass all these infrastructure costs is to simply assign the entire task of custom big data solution and analytics to big data development company. They do the work; you enjoy the benefit of predictive analysis. 

Trained Manpower

Even assuming that an organization is willing to spend a lot of money on the hardware and software side to gather and analyze big data, you still need experts with qualifications to use the software. It is a simple fact of life that there are thousands of IT professionals with some knowledge and qualifications in handling big data but not expertise at the data scientist level. Scientists are hard to source and harder to retain. The best big data analytics software simply gives you numbers. It takes a data scientist to make sense of the analytics and give results that are useful. The simple solution is to hire big data development company and you do not have to worry about any aspect of big data analytics and deriving actionable insights. 

Big Data Is About Real-Time Insights And Predictive Capabilities 

Big data benefits can be felt only when you have the capability to derive real time insights and predictive capabilities. This means high veracity, high volume and high precision handling of data inflow using tools such as visualization, computation, libraries, ETL engines and frameworks that give fast results. Real-time analytics gives insights into developing trends and helps businesses be ready for demand or to change product specs to suit evolving needs. If you cannot get these capabilities then the big data solution is not giving 100% to your organization. The solution is to let a big data development company with its capabilities take care of real-time analytics and reports that give you insights into developing trends. 

Data Security 

Data brings in its wake the issue of governance and security. Big data, by its very nature, means that data flows from different sources. The more nodes there are, the more the system is vulnerable to exploits that could lead to losses. Managing such sources and ensuring integrity as well as security call for expert governance measures. The problems arise should you opt for big data operations in house. Leave it to an outsourced big data service provider like Smart Sight Innovations and remain free from such worries. 

Upscaling

An enterprise that has put in place a system to handle big data will find that upscaling needs to be built in. This does not just refer to storage capabilities but also to processing facility and performance to be able to handle increasing loads. The solution could be to go for upgrades to system architecture but this is a never-ending process. The right answer is to simply let custom big data application development solutions provide you with the fruits of their labor while they take care of upscaling and upgrading systems. 

 

Big data is different. The challenges can be overwhelming from the financial perspective and operational contexts as well as human resources. It is cheaper and smarter to let someone else handle big data and simply use their custom big data solution to drive insights you can apply in real time and thus go one up on the competition.