Analytics / Data Science

ANALYTICS /
DATA SCIENCE

Analytics encompasses a growing field of data science capabilities including statistics,
mathematics, machine learning, predictive modeling, data mining, cognitive computing and
artificial intelligence.

Especially valuable in rich areas with recorded information, analytics relies on the simultaneous
application of statistics, computer programming and operations research to quantify performance.

Analytics encompasses a growing field of
data science capabilities including statistics,
mathematics, machine learning, predictive
modeling, data mining, cognitive computing
and artificial intelligence.

Especially valuable in areas rich with recorded
information, analytics relies on the simultaneous
application of statistics, computer programming
and operations research to quantify performance.

Analytics is the discovery, interpretation, and
communication of meaningful patterns in data

Analytics is the discovery, interpretation,
and communication of meaningful
patterns in data

There are four categories of analytics that organizations need to consider:

There are four categories of analytics that
organizations need to consider:

Descriptive
Analytics Diagnostic
Analytics Predictive
Analytics Prescriptive
Analytics

WHAT HAPPENED?

Descriptive analytics or data mining are at the bottom of the big data value chain, but it can be
valuable for uncovering patterns that offer insight. A simple example of descriptive analytics
would be reviewing the number of people that visited the company’s website over the past
few months. Descriptive analytics can be useful in the sales cycle, for example, in order to spot seasonal
trends and to adjust purchasing decisions accordingly.

WHAT HAPPENED?

Descriptive analytics or data mining are at the bottom of the big data value chain, but it can be valuable for uncovering patterns that offer insight. A simple example of descriptive analytics would be reviewing the number of people that visited the company’s website over the past few months. Descriptive analytics can be useful in the sales cycle, for example, in order to spot seasonal trends and to adjust purchasing decisions accordingly.

WHY DID IT HAPPEN?

Diagnostic analytics are used for discovery or to determine why something happened. In a
social media marketing campaign for example, diagnostic analytics can be used to determine
why certain advertisements resulted in increased conversion rates. Diagnostic analytics
provide valuable insights for organizations, because it helps them understand which decisions
impact the company’s performance.

WHY DID IT HAPPEN

Diagnostic analytics are used for discovery or to determine why something happened. In a social media marketing campaign for example, diagnostic analytics can be used to determine why certain advertisements resulted in increased conversion rates. Diagnostic analytics provide valuable insights for organizations, because it helps them understand which decisions impact the company’s performance.

WHAT WILL HAPPEN?

Predictive analytics use Big Data to identify past patterns to predict the future. From trends
or patterns in existing data sets, predictive algorithms calculate the probability that a certain event
will occur. For example, some companies are using predictive analytics for sales lead scoring,
indicating which incoming sales leads will have the highest chance of converting into an
actual customer. Properly tuned predictive analytics can be used to support sales, marketing, or
for other types of complex forecasts.

WHAT WILL HAPPEN?

Predictive analytics use Big Data to identify past patterns to predict the future. From trends or patterns in existing data sets, predictive algorithms calculate the probability that a certain event will occur. For example, some companies are using predictive analytics for sales lead scoring, indicating which incoming sales leads will have the highest chance of converting into an actual customer. Properly tuned predictive analytics can be used to support sales, marketing, or for other types of complex forecasts.

HOW CAN WE MAKE IT HAPPEN?

Prescriptive analytics is the last and most valuable level of analytics. While Big Data analytics
in general sheds light on a subject, prescriptive analytics gives you a laser-like focus to answer
specific questions. For example, in the health care industry, you can better manage the patient
population by using prescriptive analytics to measure the number of patients who are
clinically obese, then add filters for factors like diabetes and LDL cholesterol levels to
determine where to focus treatment. The same prescriptive model can be applied to almost any
industry target group or problem.

HOW CAN WE MAKE IT HAPPEN?

Prescriptive analytics is the last and most valuable level of analytics. While Big Data analytics in general sheds light on a subject, prescriptive analytics gives you a laser-like focus to answer specific questions. For example, in the health care industry, you can better manage the patient population by using prescriptive analytics to measure the number of patients who are clinically obese, then add filters for factors like diabetes and LDL cholesterol levels to determine where to focus treatment. The same prescriptive model can be applied to almost any industry target group or problem.

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Sintec Consulting + Appliance Technologies: desafiamos los límites del retail

9 July 2020/in Sin categoría /by apptec

En conjunto impulsamos Mercante como una respuesta para los retos que enfrenta el comercio minorista. Uno de los principales retos del comercio minorista es la planeación de la compra, distribución y evaluación de desempeño de los productos no-resurtibles o de temporada.