The heart of commerce is the entrepreneurial spirit, but just as important to businesses is information. The term “data” has been a business buzzword for years, but for good reason. They say that knowledge is power, and nowhere is that more true than in the pursuit of cold, hard cash. However, today’s big data infrastructure can provide perhaps too much information, making it difficult for business owners to adequately collect, store, and process data in the pursuit of bigger and better strategies. These tips can help you manage your business’s data easily and effectively.
The foundation of managing data effectively is managing the documentation of that data. Documents in myriad forms contribute to the data to which a business has access, but they also represent a crucial logistical problem that needs to be solved in order to avoid getting lost in the weeds. For starters, data needs to be accurate, and human error contributes to endless possibility for error. On the other hand, physical documents can be cumbersome, and they’re prone to getting misplaced or damaged. Likewise, the massive influx of data these days makes physical file storage all but impossible. For these reasons, digital solutions are increasingly necessary. For example, government document management software helps government employees to keep track of the information that is crucial to their line of work, whatever they may be, ensuring that their clients or employers are never left with inaccurate statistics or missing data points. The same can be true of many industries and business models. However, there are additional ways in which today’s technology can improve data management.
The Internet of Things is a nascent design philosophy, but one that has already shown it’s tremendous potential and value, for consumers as well as businesses. Simply put, IoT technology centers around connectivity and leveraging that connectivity to improve efficiency and productivity, and smart office design can be used to great effect to make a business more efficient and effective in numerous ways. For example, many IoT apps focus on data collection, storage, organization, and automation. These smart apps use artificial intelligence to replace much of the menial labor that is typically involved in such clerical processes. For example, a given application can collect data autonomously before then making the necessary calculations automatically and depositing processed, actionable data back into the greater database. Likewise, using a series of apps and/or devices, multiple systems and databases can begin to cooperate, automating even more of the processes that go into the big data pipeline.
Not unlike IoT technology, cloud technology focuses on creating a more connected way to live and and work. However, the ways in which it does so, and the problems it seeks to address, are very different. For starters, cloud storage provides users with not only additional storage space, but also more secure storage for sensitive data. By storing files remotely in the cloud, businesses can effectively hide their essential files from would-be hackers. While this is by no means a foolproof solution, on-site file storage is much easier to locate, giving bad actors a place to start looking. On the other hand, cloud computing has become an essential tool for today’s businesses, even if consumer usage of cloud computing is more niche as of yet. Cloud computing is comparable to networking but with some major differences that change the name of the game. For starters, cloud computing does away with the spatial restraints of traditional networking, and this has been beneficial to an increasing diversity of business and employment models. Most notably, the rise in remote labor has benefited tremendously from this style of networking. However, the true strength of cloud computing for businesses is that it allows a cloud “network” of computers to cooperate on shared tasks by pooling their processing power and computational assets. This has been instrumental in today’s big data infrastructure, because data analysis is a resource intensive process. With cloud computing, the burden of data processing can be divided up among several devices, allowing the project to be completed more quickly. Meanwhile, this division of labor between several devices ensures that the network and every device therein can continue to process the more mundane tasks that keep a business going from day to day while the data analysis process practically takes care of itself. However, cloud computing is only half of the battle when it comes to data analysis. Computers incredible machines capable of great things, but they can only do so much. The calculations provided by cloud computing still require the insight of a trained human eye before they can be transformed into a course of action that will benefit the company, so hiring a data analyst is potentially even more important. Only finding an actionable conclusion in the data can allow businesses use it to build better strategies moving forward.