Reflection 1 on data analysis

Reflection 1 on data analysis Data analytics maintains similarities with statistics yet they differ slightly from one another. The statistical method includes efforts to gather data and organize it for analysis purposes followed by interpretation methods to discover patterns which generate conclusions from the data. Through established methods and algorithms, the data provides understanding of its composition in addition to allowing predictions of broader populations from limited sample groups. Data analytics exists as a wider discipline compared to its counterpart. The field incorporates statistics into an approach that utilizes technology as well as computer programs alongside visual tools to extract advanced information from data. Through analytics companies receive explanations of past occurrences to predict future outcomes that ensure better decision making. The analytics field contains three fundamental categories which include descriptive analytics, predictive analytics and prescriptive analytics. Descriptive analytics displays historical information by showing trends such as sales pattern evolution. The process of predictive analytics makes progressions about upcoming trends by analyzing historical data to determine probable popular items during the upcoming season. Organizations with prescriptive analytics systems generate suggestions for improving results through specific actionable choices including price adjustments to gain more customers. These tools come together so businesses can better inform themselves in the making of better strategic decisions based on future opportunities. (Brinkmann, 2019). Analytical methods are used to process data then turn it into useful information. Sales records help organizations give a figure of customer buying habit thus turning it to personalized marketing strategies. If a business will examine supply chain information, it can handle its inventory effectively to avoid product deficits. Tools offered by excel to managers arrange data better with a visual image of showing problems and also help the managers to make quick adjustments accordingly. However, application of data grants businesses the edge over their immediate resiliency and detail to their instant adaptation to the market. Some data analytics I have worked on which is based inside an organization that tracks product sales performance and customer satisfaction levels. Sales data is presented using Excel which are used to provide the organization with an annual product trend. To collect customer’s feedback, the organization has conducted surveys, which are then analyzed to extract the most recurring complaint. The descriptive analytics is the first tool the organization has used but they do not get any profound insights from their data. Predictive analytics allows the company to predict future market trends. This helps it to stock the popular products to face unexpected customer demand surges. Thus, it would be more specific with its planning approach. Prescriptive analytics help implement marketing strategies from competitor information to keep the company competitive. There are also missed opportunities. The organization should use social media data to track customers' brand. An inspection of user website behavior would identify places where people become trapped or disinterested thus leading to better online customer journey improvements. The customer service data would provide better customer behavior understanding that assist organizations in creating customized offers. (Mandel, 2012). The organization should acquire modern analytics solutions such as Power BI to obtain value from their data management systems. This will provide interactive real-time visualization. The ability to analyze data effectively would emerge through proper training of employees. Such a mindset leads to a regular inclusion of data driven decision making in the organization. Data analytics integration gives organizations the ability to derive better decision, better operations, which increase their competitiveness in the market. Descriptive, predictive as well as prescriptive analytics for combination enables organizations to reveal the formed data as informative data that would provide them with the sustainable gains. The modern business world requires organizations to adopt data analytics because it leads to enhanced inventory control along with individualized customer treatment and quick market adaptation.  References Brinkmann, B. (2019). Comparing descriptive, predictive, prescriptive, and diagnostic analytics. Logi Analytics, May. Mandel, J. (2012). The statistical analysis of experimental data. Courier Corporation.