Nowadays, the volume of data that various industries are churning out is enormous. This is what is called big data, and comes in structured and unstructured forms. The handling of big data involves data gathering, data analysis, and data implementation. Due to the critical nature of data, data analysis has changed from being a departmental affair to a whole business. This has seen the employment of top-notch technologies and advanced analytical tools and techniques. It has become necessary for businesses to be on top of their game with the right and latest big data analytics trends to match and beat the competition. Regardless of their size, businesses are relying on data for growth opportunities, to address issues, and to operate optimally for maximum profits.
So, what are some of the top big data analytics trends for 2019 businesses should know?
1. The harnessing of dark data
Dark data can be defined as the information assets that businesses gather, process, and store over the course of their activities but that is not currently being utilized for business analysis. After acquisition through different computer network operations, the data is not used for decision-making or to give crucial insights despite spending tons of resources to have it. With the increased emphasis on data analytics and data becoming part of the daily life of a business, dark data will be given more focus since any data that is not utilized is a lost opportunity or could result in potential risk.
Businesses need the capacity to utilize all data available after proper analysis, but if they do not have the capacity, engaging experts in big data such as Active Wizards can be a good idea to remain competitive and capitalize on all opportunities presented by advanced data analysis.
2. Massive growth in IoT networks
It is expected that the internet of things (IoT) will one of the biggest trends in 2019 and the following years after having started to gain momentum in the recent past. By 2020, IoT is anticipated to generate $300 billion annually. The indication from the most recent industry trends and research reports is that the worldwide IoT market will grow at a compound annual growth rate (CAGR) of 28.5%. More than ever before, businesses will count on more data points to gather data for in-depth business insights.
3. Higher demand for Chief Data Officers (CDOs)
The profile of the chief data officer (CDO) has been taking shape over the years and it is now getting its rightful position within organizations. Human resource departments will be scouting for qualified and well-experienced people to fill this demanding and trendy position. But despite its rising demand, the position is still relatively new in most companies. People who have been leading teams overseeing overall business data cleaning, analysis, implementation, and deriving helpful insights may be well suited for the CDO position.
4. Cloud storage and optimization of cloud costs
While moving of data storage to the cloud is typically cheaper than storing it on a business premises, the cost of cloud systems can be further optimized. With this understanding, 2019 and beyond will witness more entities switching to cold data storage solutions like Google’s Nearline and Coldline and Azure Cool Blob. This will save them as much as 50% of the cost of storing older and unused data in cold storage, therefore availing cash to invest in data activities with high ROIs.
5. Edge computing
Edge computing capitalizes on proximity by processing data close to the sensors and endpoints as much as possible, hence minimizing latency and traffic in the network. It enables data to be managed and stored away from the storage setup and closer to the end-user as processing happens in the device itself, or the edge data centre, or the fog layer. Edge computing is expected to be used more in 2019 and beyond thanks to the reduced latency and lower cost of real-time data processing.
Organizations must know about these top big data trends and others and be ready to optimize them by getting prepared. They will need to have better and more flexible data platform that will automate and integrate all data sources and types as opposed to relying on their old and at times outdated traditional data systems.