September 25, 2019
According to the official data from Statista, the total amount of digital information globally is expected to comprise 175 ZetaBytes by 2025. Concepts of Big Data and data modelling, allowing hardware to collect and process tons of data from numerous sources online and fast, plays a big part in optimizing worldwide data consumption. As a whole, data modelling can come in quite handy in your business managing routine. Learn how exactly.
Big Data describes a field of technological solutions that are intended to handle one global task - process colossal amounts of both structured and unstructured data in the real-time mode. Common data modelling concepts may be put to good use in various fields, from science to commerce.
Fortunately, Big Data solutions are affordable even for small businesses to implement. In the recent past, companies had to hire whole departments of experts and organize for occasional courses focused on learning data modelling. The niche is so rapid in its development, however, that today cloud-based digital business analytics solutions managed autonomously by AI can handle it all.
Let’s find out step by step how to most properly approach the implementation of the data modelling basics in your business.
As a rule, business analytics solutions are used by every other company department for its own purposes. Add a huge number of data sources to work with today and you can see that a single product would hardly be enough to meet all the needs of all the employees.
For instance, a logistics departments could use some software based on GIS data modelling, the supply-managing team will find dimensional data modelling principles very helpful while your sales department will need a solution with the capabilities of statistical modelling for data analysis.
Thus, it would be pretty reasonable to consider the purchase of several integrative Big Data-processing, data modelling solutions from the get-go.
To provide a good competitive ability for your business, it’s crucial to set transparent, trustful relationships with clients. In this matter, you may use certain software data modeling tools that can analyze the interaction of your customer support with end consumers step-by-step and provide conclusions or predictions based on the accumulated data.
Up to date, there is a huge selection of software solutions that gather user data - social media, search engines, and various web applications. You shouldn’t neglect such galore and go for a number of such channels at once. It’s better when the data source is integratable with third-party products.
Software that features a forecasting tool will give much more than just a boost in the data processing speed. The major advantage of predictive analytics is that you get long-term predictions, on which future company goals may depend. Mostly, these goals are directed at boosting or retaining the existing level of income.
Nonetheless, as practice shows, predictive analytics in combination with artificial intelligence can go beyond the mentioned capabilities. In particular, you can identify employee turnover issues on the early stages of work and plan out further worker retaining strategy.
Thus, Watson IBM software is used to assess general factors that influence people to leave their positions. Analyzing structured data, the supercomputer defines tendencies of each separate employee and calculates the chances of them leaving.
As enterprise data modelling tools, obviously, contain tons of regularly updated info, it’s pretty difficult for a regular person to focus on everything that’s going on. That’s why it’s important to have a software tool at disposal, which would help you visualize the collected information for certain periods of time. That’s how you get to accessibly see ‘the big picture’.
The more your software is accessible to users, the better. I.e., it’s great when your employees or project mates are able to access an app project from any device connected to the web and check the relevant data. That’s where cloud storage will come in more than handy.
Considering the all-around availability of Big Data solutions, their suppliers should be able to guarantee a sufficient level of security for their users. In fact, the security of a virtual user environment is among the basic elements lying in the foundation of the software provider’s business. That’s why the provider’s responsibility before a client company is usually regulated by a Service-Level Agreement (SLA).
Before purchasing a license for some software, make sure that your service provider employs specialized software products and hardware means of data protection in cloud.
It doesn’t matter on which stage of development your business currently is. In any case, you can probably use a reputable source of objective, relevant info to guide you in your decision-making. In this aspect, we can return to helpful Big Data visualization tools, which allow to visually assess the dynamics of company growth building interactive charts within seconds.
Summarizing our brief data modelling tutorial up, as you can see, implementation of common data modelling techniques and integration of solutions based on them is quite an accessible task even for a small business. If you plan on starting up a Big Data project, contact us and we’ll create you a scalable, reliable yet affordable and user-friendly product that is guaranteed to meet your highest expectations.
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October 9, 2019