Data Analytics

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Today we will touch the most up to date science of the world: Data Analytics. In modern times, mass storage of data and its application to the relevant fields has given rise to the term data analytics. We think every person should know about this science even should understand what it is, for built shining future. We will try to explain this size in simple way and with short samples.


In modern times, mass storage of data and its application to the relevant fields has given rise to the term data analytics. It reflects a variety of applications from data mining, business intelligence (BI), reporting and online analytics (OLAP) to various specialized types of analytics.


Initiatives in data analytics can help companies increase sales, improve operating performance, automate marketing strategies and customer service activities, respond quicker to new market trends and become more competitive. Depending on the specific program, the data analyzed may include old data or new data developed for use by real-time analysts.


What is data?


Data is any collection of characters gathered and interpreted, typically analyzed for some purpose. When data isn't put into context, a person or a machine doesn't get anything from it. Data are the facts or details from which information is derived. For data to become information, data needs to be put into context. Data is raw, unorganized facts that need to be processed. It can be something simple and seemingly random and useless until it is organized.

Example: Each employee's start and finish time of work is one piece of data. The average working hours of employees is information that can be derived from the given data.


What are Analytics?


Analytics is the identification and analysis of important trends in data. Analytics uses data and math to address business questions, to find connections, to forecast unpredictable outcomes, and to automate decision taking.


Data analytics


Data analytics (DA) is the process of analyzing data sets to draw conclusions about the knowledge found therein, increasingly with the help of advanced systems and software. Data analytics as a term primarily refers to a variety of applications, ranging from simple business intelligence (BI), reporting and online analytical processing (OLAP) to various types of advanced analysis. Data will help businesses understand their consumers better, improve their promotional strategies, customize their content and improve their bottom lines. The benefits of data are numerous, but without the proper data analytics tools and processes, you can't access such benefits.


Data analytics tools


Advanced data analytics tools allow users to access, integrate, communicate with, analyze, and visualize data from any variety of sources, giving them deeper insight into their business processes, their markets, and their customers. The most modern analytical system programs are Excel, MS Power BI, Office 365 package, etc. At the same time, in order to be able to analyze data analytically, a data must understand a number of database structures, be able to compare them, and know how to obtain (draw) data from a source. Today’s the most using tool for visualization of data is Power BI.


Power BI 


Power BI is a business analytics service by Microsoft. It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards. Power BI provides cloud-based BI (business intelligence) services, known as "Power BI Services", along with a desktop based interface, called "Power BI Desktop". It offers data warehouse capabilities including data preparation, data discovery and interactive dashboards


Benefits of Data Analytics


There are a lot of benefits of DA in workplace and Data Analytics shows its benefits in different sectors in the world.Ability to make faster, more informed business decisions, backed up by facts. Deeper understanding of customer requirements which, in turn, builds better business relationships. Increased awareness of risk, enabling the implementation of preventative measures. Improved flexibility and greater capability in order to react to change - both within the business and the market. Better insight into the financial performance of the business. Proven to reduce costs and therefore increase profit.


Data Analytics Financial


In the Banking and Financial Services sector, through data analytics, institutions can monitor and assess large amounts of customer data and create personalized/customized products and services specific to individual consumers.

Banks uses Data analytics for : Managing customer data, Personalized marketing, Customer segmentation, Customer spending patterns, Fraud detection and etc.


Data Analytics in Medicine and Healthcare


Data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various – omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomes, pharmacogenomics, diseasomics), biomedical data and electronic health records data.


Data Analytics in Government


The public sector or government agencies are known for generating and using vast quantities of data. Big analytics provides the government departments with an ability to save public funds. The federal government can save billions per annum by using data analytics effectively.


Data Analytics in Tourism


Tourism boards and companies in the tourism sector can benefit from data of this type in many ways. This involves defining marketing strategies, delivering packages tailored to the possible desires of travelers, and determining on which countries to concentrate on winning clients.


Data Analytics in Education


We can be used to estimate in-class students grades. When the model determines that the student will have a weak CGPA based on such parameters obtained then the model will produce a alert to the teacher suggesting that the student will have to work harder to achieve the target level. The teacher will know in what topic a student is poor and execute study plans for him


Data Analytics in Hospitality


For information about how to keep their clients satisfied, hotel and leisure operators look to sophisticated analytics tools. A growing use of analytics in the hotel industry is for yield management. It is the way to ensure that each room attracts the best price – taking into account year-round droughts and demand peaks, as well as other factors, such as weather and location.


In recent years, the field of analytics in the world has already developed and the requirements for this development are obvious. The main reason for this development is the presence of large companies and corporate companies in the country, and such companies also see the significant impact of analytics on their market. As a result, the widespread development of a market economy in the world leads to the development of this area as well.

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