Data analysis is defined as a process of cleaning, transforming, and modelling data to discover useful information for business decision-making. The purpose of Data Analysis is to extract useful information from data and make the decision based upon the data analysis. Here are some 5 reasons to invest in data analysis below. Data analysis is used to evaluate data with statistical tools to discover useful information. A variety of methods are used including data mining, text analytics, business intelligence, combining data sets, and data visualisation.
There’s greater access to sophisticated analytics, such as AI, as well as third-party data that fully illuminates the digital footprints of online customers. Decision-makers can now study more factors, including affluence, different levels of price sensitivity, affinities to different brands, and key behaviour traits of potential customers. One large European insurance company is even using analytics to segment millennials. Instead of segmenting this important group solely by age, the company has identified 87 different subgroups within the millennial demographic, all with different needs. Such insights are impacting this company’s product development strategies
Data provides early warnings about production and service problems, ultimately leading to higher quality products. By analysing customer engagement, companies can better understand the concerns and changing desires of consumers, and innovate products accordingly. Companies can align service delivery with all functions of the business and improve production and quality control.
According to a survey, it is known that almost 75% of the companies worldwide have already invested or are planning to invest in big data analytics. As the competitors are already making use of this powerful tool and becoming more data-driven, this trend will soon become a necessity rather than an option for businesses to cut through the competition. Therefore, it is important that you too utilise this opportunity to stay ahead of your competitors in the market.
When utilising big data sets, companies can conveniently opt for cloud service providers for storage and computing power. Cloud-based solutions help companies to analyze large piles of data without any kind of investment in hardware. Consequently, most of the companies today are using cloud-based solutions to store and process huge data sets and leverage it as required for analytical applications. SovTech offers pristine Cloud hosting, Maintenance and Security Solutions.
Monetising data is expected to become a hot topic in the coming years. Companies already know the value of data internally, as data is commonly known as a digital gold in the industry. The next step for the organizations would be to maximize economic benefits from the collected data with the help of external sources, partners, suppliers, and customers. The opportunities to derive value from data are abundant and have to be tapped by the businesses.
The few key steps and below are imperative when it comes to Data Analysis and the payoff is finding results!
A dedicated product scientist is imperative to take you through the motions above implementing what is relevant to your business.
The Product Scientist is SovTech’s answer to helping our clients understand specific data and analytics about their platforms and how to use this information and data to improve their products. Our Product Scientists create custom engineering road-maps determining the product’s building blocks, to enable new feature creation and expansion. This will enable clients to visualise features discovered, that will fit into the series of developmental sprints.
To conclude it is imperative to always align insights with your overall business objectives (on and offline), data by itself is a great way to see how you are performing, but without applying what you’ve learned, it has little use.
