Data Analytics is the process of analyzing raw data with the objective to gain useful insights and patterns from it. In addition, it helps in optimizing business performances and finding efficient ways to do business.
Types Of Data Analytics
Data Analytics has 4 types that are as follows.
- Descriptive – This analytics provides answers to the question “What Happened”. In addition, they act as the backbone of reporting.
- Diagnostic – It answers the next logical question ” logical question, “Why did this happen”. It further helps in understanding the root cause of an event.
- Prescriptive – It helps in knowing “What might happen in the future”. In addition, in this analytics, AI and Big Data combine to predict outcomes.
- Predictive Analytics- This analytics answers ” What should we do next”. In addition, it helps in identifying trends, correlations, and causation.
Methods & Techniques Of Data Analytics
- Regression analysis- This analysis estimates the relationship between variables. In addition, it determines how changes to one variable affect the other.
- Factor analysis- It is useful in reducing the data into smaller forms. In addition, it is helpful in businesses to determine customer loyalty.
- Cohort analysis- It is useful in breaking a dataset down into groups that share common characteristics. In addition, it helps in knowing customer segments.
- Cluster analysis-This analysis technique helps in classifying the objects into groups called clusters. It is useful in revealing the structures in data.
- Time series analysis- It is beneficial in finding trends and cycles over time. In addition, it has multiple uses for economic and sales forecasting.
- Sentiment analysis- The primary objective of this analysis is to interpret and classify qualitative data by organizing it into themes. It helps in understanding how a customer feels about a product or service.
Features Of Data Analytics
Data Analytics helps in improving business-related decisions by eliminating guesswork. In addition, it helps a business by providing it various insights about the ongoing trends and future happenings. Thus, leading to better customer satisfaction along with making informed data-driven decisions. To further know about it, one can visit the Data Analytics Online Course in Qatar. Apart from these, given below are some of the features of Data Analytics.
- Helps in Business Intelligence & Reporting- This technology helps in analyzing data with the objective to provide insights for better business decisions.
- Data Wrangling/Data Preparation- It is capable of preparing and wrangling data so that it can be easily accessed from a variety of data sources.
- Data Visualization- Visualization is the graphical representation of data. In addition, it helps in exploring and identifying patterns and outliers in a data set.
- Geospatial and Location Analytics- These analytics help in developing insights and spot relationships in the data you are unaware of. In addition, it also helps in making predictions.
- Machine Learning- It is the process of using algorithms to learn from data. In addition, it helps in boosting performance by finding trends and insights with the use of computers.
Uses Of Data Analytics
Data Analytics is capable of detecting anomalies and managing customer data. In addition, it also helps in managing risk and detecting fraud. Moreover, it also has uses in analyzing operations and performing market research. Many institutions provide Data Analytics Online Certification in Dubai and one can enroll in them to learn its functions and start a career in it. Given below are some of the applications of this technology in the real world.
- Retail- In retail sectors, Data Analytics helps in understanding the needs and buying habits of customers. In addition, it helps in predicting trends and developing new products for customer satisfaction.
- Healthcare- Healthcare industries use this technique to develop better diagnoses and treatment facilities. Moreover, it also helps in finding new drug development methods as well.
- Manufacturing- Manufacturing sectors use this technique to solve complex supply chain issues, labor constraints, and equipment breakdowns.
- Logistics- It is useful for logistics companies as it helps in developing new business models and optimizing routes.
- Banking Sectors- Data Analytics is capable of finding out fraudulent transactions. In addition, it also helps in knowing the details about the probable loan defaulters.
Tools For Data Analytic
Given below are the best tools.
- R and Python.
- Microsoft Excel.
- Tableau.
- RapidMiner.
- KNIME.
- Power BI.
- Apache Spark.
- QlikView.
