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Data Analytics

Analyzing data helps business users make informed decision for the development of your business. While analyzing data, you need to have a precise goal in order to get an effective analytics. In ITReview, we are used to saying ”data speak for themselves, you just need to let them speak by asking them the right questions and creating the right conditions”. So, what is your target market? Or what is the purpose of the analytics?
Depending on market fields and goals, the data collected in the elaboration phase are analized and managed through the visualization of trends. From data, you will be provided with real parameters to understand the information value and identify KPIs (Key Performance Indicators) as hands-on guidelines in the decision-making process.

Understanding data is the first step for a strategic planning

Looking for better understand past phenomena or forecast new trends? Depending on your goals, you have four types of analytics, but across them there’s a common golden rule: data command, they have to be interpreted to obtain consistent answers and finally take informed decisions.

Il dato risponde alla domanda “Cosa è successo?”

Descriptive Analytics

Answering to the question What happened?

Descriptive Analytics manages data come from multiple sources such as polls, reports, or past events to give insights into the past and extract previously unknown patterns. It may be useful to understand the sentiment analysis of a social media campaign or measure its overall performance in terms of reactions and comments.

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Il dato risponde alla domanda “Perché è successo?”

Diagnostic Analytics

Answering to the question Why it happened?

The loss of a customer or an exponential sales growth are phenomena to be understood by the company. Through drill-down and correlations, Diagnostic Analytics uses different data sets to determine the relationship between variables, or causes and effects.

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Il dato risponde alla domanda “Cosa potrebbe succedere?”

Predictive Analytics

Answering to the question What is likely to happen?

Considering the liquid business scenario, the understanding phenomena and consumers’ needs may let you gain a strong competitive advantage. Through custom algorithms created with R and Phyton and the Machine Learning process, predictive analytics uses the findings of descriptive and diagnostic analytics to predict possible outcomes based on the analysis of trends and past events.

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Il dato risponde alla domanda “Come reagire a potenziali eventi futuri?”

Prescriptive Analytics

Answering to the question What do you need to do?

Data help you determine the best course of action to take, i.e. in order to avoid any risk of producing products for which there is no demand or find a new niche market. Since you have a precise goal, the prescriptive analytics uses data in the most complete way. By analysing trends and learning from past behaviours, it gives advice on potential outcomes and help companies make decisions.

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Data Analytics 1
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