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A way to explore large volumes of data, to get insights, answer questions, create solutions and solve problems that are impacting overall success.
- Data Science
- Python
- Jupyter Notebook
- IBM Watson
- Data Analytics
- Data Visualization
- Machine Learning
- Model Development
- Predictive Analysis
- Classification
- Segmentation
- Data Mining
- Web Scraping
- Market Research
- Business Insights
- Performance Optimization
- Digital Manufacturing
- PLC
- Machine Processing
- Automation
- Cloud-Based Architecture
- Cloud Migration
- Cloud Computing
- Virtual Machines
- Back-Up Services
- Serverless Computing
- Web Application Development
- Mobile App Development
- IoT – Internet of Things
- AWS Cloud
- IBM Cloud
How companies can get started in Data Science
Businesses know one thing and that is if they aren’t able to measure performance then they are not able to improve it.
If they are unable to measure their costs, they are unable to reduce them.
If they are unable to measure their profits, they are unable to increase them.
A company has to start recording information, capturing data about costs, labour costs, material cost, how much it costs to sell one product, the total cost and then look at the revenue. Where’s your revenue coming from? Is 70% of your revenue coming from 30% of your customers? Or is it the other way around?
Once you have data, then we can apply algorithms and analytics to it.
If you’re capturing data, archive it. Do not overwrite on old data thinking you don’t need it anymore. Data never gets old. Data is always relevant, even if it’s 100 years old. It is relevant to you and your firm and your success.
Make sure nothing goes to waste. Make sure there’s a consistency. Someone 20 years later trying to understand that data should be able to do so. Put the best practices for data archiving in place.
Start measuring things.
Too many companies won’t measure things properly for years and then they will decide they want data science. Data science is only going to be as valuable as the data collected. Garbage in, garbage out is a rule in any sort of analysis.
Data Science is making an impact on businesses and is changing day to day operations, financial analytics and interactions with customers.
It’s clear that businesses can gain enormous value from the insights Data Science can provide, but sometimes it may seem hard to see exactly how.
In this era of Big Data, almost everyone generates masses of data every day, often without being aware of it. This digital trace reveals the patterns of our online lives.
If you have ever searched for or bought a product on a site like Amazon, you will notice that it starts making recommendations related to your search. This type of system, known as a Recommendation Engine, is a common application of Data Science.
Companies like Amazon and Netflix use algorithms to make specific recommendations derived from customer preferences and historical behaviour.
Personal assistants like Siri on Apple devices use Data Science to devise answers to the infinite number of questions end users may ask.
Google watches your every move in the world, your online shopping habits, and your social media. Then it analyzes that data to create recommendations for restaurants, bars, shops, and other attractions based on the data collected from your device and your current location.
Wearable devices like Fitbits, Apple watches, and Android watches add information about your activity levels, sleep patterns, and heart rate to the data you generate.
Data Science has become the key basis of competition and is supporting new waves of productivity, growth, and innovation.
Take UPS which is using data from customers, drivers, and vehicles in a new route guidance system aimed to save time, money, and fuel. Initiatives like this support the statement that Data Science fundamentally changes the way businesses compete and operate.
How a firm gains a competitive advantage
Take Netflix as an example. Netflix collects and analyzes massive amounts of data from millions of users, including which shows people are watching at what time of day, when people pause, rewind and fast-forward, and which shows, directors, and actors they search for.
Netflix can be confident that a show will be a hit before filming even begins, by analyzing users’ preference for certain directors and acting talent and discovering which combinations people enjoy. Add this to the success of earlier versions of a show, and you have a hit.
Thanks to Data Science, Netflix knows what people want before they do.
Some more ways Data Science is used, for example, it helps physicians provide the best treatment for their patients and it helps meteorologists predict the extent of local weather events, and can even help predict natural disasters like earthquakes and tornadoes.
The purpose of Our Services
Data Science is the process of using data to understand different things, to understand the world, and is the art of uncovering the insights and trends that are hiding behind data.
Our Services are there to communicate new information and insights from the data analysis to key decision-makers.