Data Analysis
In the era where our surroundings are enriched with data, understanding how to analyze and extract true meaning from our business’s digital insights is one of the primary drivers of success. In spite of the enormous volume of data we create every day, merely 0.5% does actually get analyzed and used for data discovery, improvement, or even for intelligence. Well, it may not seem like much, considering the amount of digital information businesses have at their fingertips, so to help you comprehend the potentiality of analysis, the meaning, and how you can employ it to enhance your business practices, we are here to explore data analysis methods and techniques for you.
The various methods involved in the process of collecting, modeling, and analyzing data to extract insights that support decision-making, is what concludes data analysis. We at ixiono help you gain a better understanding of different techniques for data analysis, and methods in quantitative research, as well as qualitative insights, that will give you information for analyzing the efforts towards a more clearly defined action.
Today, if you want to be in the long haul of business, you definitely want to know your customers, so by using data analysis we help you get a 360° vision of all aspects related to your customers, you can understand which channels they use to communicate with you, their demographics, interests, habits, purchasing behaviors, and a lot more. In the long run, it will drive success to your decided marketing strategies, also let you identify new potential customers, and then that will let you avoid wasting resources on targeting the wrong people or sending the wrong message. You can then also track customer satisfaction by analyzing your client’s reviews.
DATA ANALYSIS APPROACH BY ixiono
Different Data Analysis Methods
Our Experts first use different methods before diving more in-depth for appropriate analysis since it is important to ensure the reliability and validity of data, data sources, data analysis methods, and inferences derived. Our approach here involves ‘why,’ ‘what’ and ‘how’ first which further proceeds to analysis in terms of numbers.
Our work includes extraction of machine-readable facts, performing several statistical operations to quantify the data, diagnose analysis and eventually it comes to predictive analysis where we use historical data and feed it into the machine learning model to find critical patterns and trends.
Different Data Analysis Techniques
Different techniques that are taken into account for Data Analysis depend upon the problem we have in hand, the kind of data, and the proportion of data gathered. We apply techniques based on Mathematics and Statistics, Artificial Intelligence and Machine Learning, and Visualisation and Graphs. Each of these techniques we use, focuses on processing the new data, mining information from data, and turning down that information to transform facts and figures into decision-making parameters.
Different Tools for Data Analysis
With the availability of different tools in the market, we intend to operate with the best of them. Before choosing any data analytical tool, we comprehend and essentially consider the scope of work, infrastructure limitations, economic feasibility. Our experts work with Microsoft Excel, Tableau, R & Python, Power BI, and SAS.
Regression Analysis
A type of quantitative data analysis technique that determines the relationships between independent and dependent variables. Through experiments that involve manipulating the values of independent variables, our data analyst at ixiono assesses the impact of the changes on the dependent variable. This process, you can think of it in terms of cause and effect. And at the end of the test, our data analyst draws a conclusion based on the results.
Content Analysis
Another approach, content analysis, a qualitative data analysis technique that is built on two main qualitative data approaches: deductive and inductive. We use content analysis to identify patterns in various forms of communication as content analysis can reveal patterns in recorded communication that indicate the purpose, messages, and effect of the content. In this procedure, we study the relationships between the particular keywords to better understand the hidden intention behind the messages.
Statistical Techniques for Data Analysis
Here in particular we use mathematical approaches to get insights, observations, and conclusions and the process encompass testing hypotheses and making estimates and predictions of unknown data or quantities. Statistical techniques for data analysis help out in various ways, such as determining the risk of different business scenarios or even in forecasting sales while there are changes in market conditions. The data is generated every day by users and statistical analysis of those data reveals insights from tables populated with a lot of data.
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