DATABERG
Data is proliferating at an unprecedented rate. As a result, data access is becoming one of the most pressing issues for corporations of any scale.
Businesses can obtain data from numerous sources, including IoT, AI, and a wealth of other emerging technologies. Whenever consumers interact with Internet – whether through search engines, social media or apps – they produce a phenomenal amount of data. This dramatic influx of information known as big data presents incredible opportunity and major challenges. For instance, marketers have access to vast amounts of customer data. However, this data presents issues for existing IT infrastructures. Velocity, variance, and volume of big data make it challenging for dated business systems to handle all the tasks.
Moreover, the issue is only becoming more pronounced. Many organizations still lack sufficient tools to extract business intelligence from big data. Whilst there are solutions to manage volume – for instance, shifting big data management to public cloud providers – it is still essential that staff is data literate. In the long term, a data-driven corporate culture will be essential to maintain a competitive edge. Therefore, it is essential for the employees to come to grips with data access, management, and analysis. Although integrating data into business processes is a long-term endeavour, there are four essential steps of the data handling process, which will benefit every level of the organization.
1. Automated systems
Real-time analytics is critical to success. Manual data capture and process inevitably extends delivery times, which comprises the value of the information. Therefore, businesses need to implement solutions that automatically migrate and manage data from different sources, with emphasis on the most active platforms.
2. Data quality
The value of data depends on its quality. This is directly linked to how useful the data is, as well as its structure and relevance. Subsequently, it is important to make sure data is visualized clearly and concisely. Senior executives are unlikely to have the time to study detailed documents to make sure the insights are presented in a legible format. Moreover, visualization also illustrates the correlations between large data sets faster that means business decisions are made with greater agility.
3. Data access
When considering data solutions, it is important to make sure software caters to the needs of all departments and all degrees of expertise. For instance, some departments may only need fast access to visualizations. In contrast, IT managers or data teams may require the ability to generate their own reports or develop specialized protocols. Moreover, as the velocity of business processes increases, it is critical that employees can access intelligence across different devices. Therefore, it is essential that a company’s data management solution is mobile-ready.
4. Clarity
Big data tools should enable businesses to gain insights faster. Therefore, it is important to select data management software that facilitates this aim. For example, technology that requires hours of training to understand is likely to frustrate and alienate employees. Furthermore, if the IT department needs to spend substantial amounts of money on training, it can damage the ROI the product represents.
Fight fire with fire
Advanced technology has created big data, and it takes advanced technology to address the problems it presents. Therefore, selecting the right big data solution is essential to enhancing business strategy. An effective solution should facilitate greater data access and ease of interpretation.
Most industry leaders acknowledge the potential of big data, however, they remain hesitant to begin reaping the rewards. This is often down to the concerns around privacy, regulations, and the resources required to manage vast swathes of data. However, with the right data solutions partner, businesses can address the key technical obstacles, empower staff, and ensure secure, dependable data access.
