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Data science: are you using your data effectively to improve your business?

By September 15, 2020No Comments

Data science: are you using
your data effectively to
improve your business?

  15/09/2020

Data science: are you using your data effectively to improve your business?

15/09/2020

Introduction:

In 2018, the Global Datasphere reached 33 zettabytes but in 2025, the Datasphere will grow to 175 zettabytes. This means that the growth will be 430,303%

But you might be thinking, what even is a zettabyte? A zettabyte is 10 21 or 1,000,000,000,000,000,000,000 bytes, if you prefer long numbers. More simply, Gartner says that if you want to download 175 zettabytes at the average current internet connection speed, it would take you 18 billion years to download. Even if everyone on the planet accepts to help you with the download, it would take 81 days. That’s why today, the main concern for the companies is no more how to collect the data but how to use it.
That’s why data science is the future of the data.
That’s why, in this article we’re going to see what data science is, for whom it may be useful and how to do it.

Benjamin Zammit
Business Unit Leader
Fact: When I wake up I do 5 minutes of skipping.

ABOUT ONEST  

Data sciences, tomorrow’s biggest business challenge

External, internal, big data, small data, observational, experimental… Everything is data for business today. Surrounded by Artificial Intelligence, real-time data, dashboard, the real challenge is to know how to improve your business with it. And, in fact data only is not going to help you make the best decision for your business. A study by Deloitte (2014) showed that companies believe that barriers to using data effectively are most commonly related to a lack of quality, 67% of the time . Most companies have jumped into data, without really knowing what they were searching, so much so that nowadays a lot of companies are drowning under the amount of data… And that’s where data science became the only solution for business. Data science and data scientists have become one of the most in-demand services and jobs for companies: in 2011 the job listings for Data Scientists has already increased by 15,000% so imagine today.

We based our business choice on data, not anymore only on luck or our experience, in a world where everything is changing at breakneck speed. That’s why a lot of companies are turning and proclaiming themselves as “data-driven companies” and it became a famous term today. Companies that have already dealt with the difficulties of data analysis have already had to make their transformation. But what type of company uses data science today? In fact, all industries: public sector like healthcare and transport but, mostly private sector like finance, retail, eCommerce, manufacturing, banking etc.

So Data analysis is globally used to help organizations make better decisions. Data analysis can help companies: sales, marketing, finance, and all the data you can get from a company’s activities like fraud detection, maintenance scheduling or Marketing (segment and identify customer, strategic marketing decision making, recommending product).

The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it that’s going to be a hugely important skill in the next decades. – Hal Varian, chief economist at Google and UC Berkeley professor of information sciences, business, and economics.

How data sciences are used in business?

Traditionally, data science is declined in a life-cycle of 6 stages.
First step is to define your problem: what do you want to know, to track? It’s the most important step if you want to start data analysis without wasting money on nothing much you need to find out your business pain points if you don’t see them already. Data scientists can help you to find a problem to solve but they need a minimum of guidance.

The next step is to capture the data. Today it might seem like the easiest step with all the technology and computer capabilities that have been growing all the time. But, you need to pay attention to the data you collect, how useful it is, how much it is, how it relates to your goals, otherwise you may have problems at the next step… The sources of error can be multiple: missing data, wrong information, inappropriate data, non-conforming data, duplicate data and poor entries. Then you have to maintain them . It means store, clean and class them to prepare it for proper use. When your data is available you can then process them by exploring, classified, modelling and summarising them. At this stage, your data is usable. That means that you can now analyse it by exploring them further, predict analysis, regression*, text mining and do qualitative analysis.

The last step is the most important for corporate decision-makers: communicate. That’s where the magic happens and an excellent data scientist will make the difference: understand the data and make it understandable. Communicating in the data process is about data reporting, data visualization, business intelligence and decision making. It’s crucial that people clearly understand the result and know how to interterprate them properly to make the best decision to react.
Data analysis seems to have become the key to making the right business decisions today. Did you know that the average organization is losing $13.5 million per year as a result of poor Data Quality? (Gartner, 2015) .

Benjamin Zammit
Business Unit Leader
Fact: When I wake up I do 5 minutes of skipping.

ABOUT ONEST  

In 2018, the Global Datasphere reached 33 zettabytes but in 2025, the Datasphere will grow to 175 zettabytes. This means that the growth will be 430,303%

But you might be thinking, what even is a zettabyte? A zettabyte is 10 21 or 1,000,000,000,000,000,000,000 bytes, if you prefer long numbers. More simply, Gartner says that if you want to download 175 zettabytes at the average current internet connection speed, it would take you 18 billion years to download. Even if everyone on the planet accepts to help you with the download, it would take 81 days. That’s why today, the main concern for the companies is no more how to collect the data but how to use it.
That’s why data science is the future of the data.
That’s why, in this article we’re going to see what data science is, for whom it may be useful and how to do it.

External, internal, big data, small data, observational, experimental… Everything is data for business today. Surrounded by Artificial Intelligence, real-time data, dashboard, the real challenge is to know how to improve your business with it. And, in fact data only is not going to help you make the best decision for your business. A study by Deloitte (2014) showed that companies believe that barriers to using data effectively are most commonly related to a lack of quality, 67% of the time . Most companies have jumped into data, without really knowing what they were searching, so much so that nowadays a lot of companies are drowning under the amount of data… And that’s where data science became the only solution for business. Data science and data scientists have become one of the most in-demand services and jobs for companies: in 2011 the job listings for Data Scientists has already increased by 15,000% so imagine today.

We based our business choice on data, not anymore only on luck or our experience, in a world where everything is changing at breakneck speed. That’s why a lot of companies are turning and proclaiming themselves as “data-driven companies” and it became a famous term today. Companies that have already dealt with the difficulties of data analysis have already had to make their transformation. But what type of company uses data science today? In fact, all industries: public sector like healthcare and transport but, mostly private sector like finance, retail, eCommerce, manufacturing, banking etc.

So Data analysis is globally used to help organizations make better decisions. Data analysis can help companies: sales, marketing, finance, and all the data you can get from a company’s activities like fraud detection, maintenance scheduling or Marketing (segment and identify customer, strategic marketing decision making, recommending product).

The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it that’s going to be a hugely important skill in the next decades. – Hal Varian, chief economist at Google and UC Berkeley professor of information sciences, business, and economics.

What data can do for you

Retail and ECommerce

Identifying customer
Customer segmentation
Strategic Decision Marketing
Recommending product
Analysing reviews

Healthcare

Medical Image Analysis
Bioinformatics
Drug Discovery
Virtual Assistant

Manufacturing

Predictive maintenance
Anomaly detection
Maintenance scheduling
Purchase order automation

Transport

Self Driving Car
Enhanced Driving Experience
Car Monitoring System
Enhanced safety of passengers

Banking

Fraud detection
Credit risk modelisation
Customer Lifetime value

Finance

Algorithmic trading
Risk analytics

Gaming

Game optimization
Analysis of the player’s game
Prediction

What data can do for you

Retail and ECommerce

Identifying customer
Customer segmentation
Strategic Decision Marketing
Recommending product
Analysing reviews

Healthcare

Medical Image Analysis
Bioinformatics
Drug Discovery
Virtual Assistant

Manufacturing

Predictive maintenance
Anomaly detection
Maintenance scheduling
Purchase order automation

Transport

Self Driving Car
Enhanced Driving Experience
Car Monitoring System
Enhanced safety of passengers

Banking

Fraud detection
Credit risk modelisation
Customer Lifetime value

Finance

Algorithmic trading
Risk analytics

Gaming

Game optimization
Analysis of the player’s game
Prediction

How to use data sciences in your business?

Data science is like most of the services that you find in organization a choice: recruit or outsource. And like most services that are not part of your expertise, you ask yourself the same questions:

Obviously the cost: is this activity a part of your expertise? Will hiring someone to do this job save you money? Will they do a work of quality equivalent to professionals? This is a demanding field where you can directly see the difference between a good and an average Data Analyst. Do you have an employee or a team to dedicate to this? For most organizations, even big companies, it’s better for them to outsource this activity for multiple reasons:

High-quality service

Benefits of the expertise of an entire team of professionals dedicated to your problem and have the experience to do work with similar companies.
Benefit from the expertise and directly usable work without being a data specialist.

High-quality service

Benefits of the expertise of an entire team of professionals dedicated to your problem and have the experience to do work with similar companies.
Benefit from the expertise and directly usable work without being a data specialist.

The cost

Outsource this activity will first of all save you time therefore money!

Software engineers, project managers, and database specialists are high-income occupations. Equipment like professional hardware and software also have a significant cost.

The cost

Outsource this activity will first of all save you time therefore money!

Software engineers, project managers, and database specialists are high-income occupations. Equipment like professional hardware and software also have a significant cost.

Security

Specialized agencies use specialized and secure tools. They are obliged to ensure the confidentiality of your data. The company and their teams are subject to confidentiality agreements. Concretely, your organization can be greatly advanced with data science because, like we saw earlier, data science is everywhere, in every activity: retail, finance, and even public sector. If you do not yet have a clear strategic plan with concrete issues regarding data analysis, you should strongly consider…

Security

Specialized agencies use specialized and secure tools. They are obliged to ensure the confidentiality of your data. The company and their teams are subject to confidentiality agreements. Concretely, your organization can be greatly advanced with data science because, like we saw earlier, data science is everywhere, in every activity: retail, finance, and even public sector. If you do not yet have a clear strategic plan with concrete issues regarding data analysis, you should strongly consider…

About Onest:

Onest help your organization to make effective strategic decisions to achieve your business goal by leveraging your data.

Our core business is Data activation: market research, survey, customer and employee satisfaction, persona, data gathering and analysis, dashboard and much more always tailored to the customer’s needs. Onest work with different types of industry: retail, health, government, games and tech etc. If you want to know more about Onest and all the possibilities for you to leverage your data, visit our website or contact us at [email protected]

Annual size of the global Datasphere

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