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Data science a glance
The document discusses the exponential growth of data, highlighting that 2.5 exabytes are produced daily as of 2017 and provides various industry use cases for data science across sectors such as healthcare, finance, and public safety. It outlines the role of data scientists, emphasizing their ability to turn data into actionable insights using advanced analytics, machine learning, and visualization techniques. Additionally, it describes the skills required to become a data scientist and characterizes the profession as a blend of statistics and software development.
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Data science a glance
- 1. Data Science ata glance Adekunle Babatunde Big Data Academy Nigeria
- 2. The Data deluge Imagefrom the Economist ➔ In 2010, Li & Fung, a firm that manages supply chains for retailers, saw 100 gigabytes of information flow through its network each day ➔ According to one estimate, mankind created 150 exabytes (billion gigabytes) of data in 2005. Before 2017 ➔ For every day of 2017 about 2.5 Exabytes of data are being produced. ➔ We perform 3.5 searches per day and 1.2 trillion searches per year, each having its’ own store in a database somewhere. ➔ 1.4 billion smartphones shipped as at March, 2017. 2017
- 3. Data in 2016and 2017
- 4. What Data an do Foundaround the house! ● Tell you what’s likely to happen ● Find unexpected Relationships ● Monitor a Situation as it develops ● Fix a problem before it becomes a crisis
- 5. Industry Data Usecases 1. Understanding and Targeting Customers 2. Understanding and Optimizing Business process 3. Personal Qualification and Performance Optimization 4. Improving Healthcare and Public Health 5. Improve Sport Performance 6. Improving Science and Research 7. Optimizing machine and device performance 8. Improving Security and Law Enforcement 9. Improving and optimizing cities and countries 10. Financial Trading
- 6.
- 7. Data and Data Sources DataScientists in the loop Business Benefit
- 8. A Data Scientistturns data into Actionable Insight. ● Data Scientist Collects Data ● Data Scientists process Data ● Data Scientists apply machine learning Algorithm and Visualizaiton Techniques to Data ● Data Scientist reports and monitor observations from data What Affects the job of a Data Scientist ● Data Sources ● Data Volume ● Technological prowess ● Technical knowledge ● Infrastructure knowledge ● Business knowledge and Business Environment Data Scientists in the data World Technical Definition of a Data Scientist : ➔ The data scientist role is an offshoot of the Statician role that includes the use of advanced analytics technologies, including machine learning and predictive modeling to provide insights beyond statistical analysis. ➔ It’s a role often said to be someone who knows Statistics more than a Software Developer and knows Software development more than a statistician
- 9. A Data ScintistSkill Chart
- 10. How to becomea Data Scientist
- 11. Conclusion Welcome to theJourney of a life time. Welcome to being a Kickass Data Scientist.
Editor's Notes
- #3 As a Data Scientist, the first question that should pop up in your mind with this statistics is What are all the data used for How do we make sense of the Data What procedure is used to achieve whatever the data is used for When is data usually collected and what is the process of collection. Notice in your task as a potential Data Scientist that their is a revolving word “data” there
- #4 This is data generated over wireless in the 2 years compared. And all these are potential points for analysis.
- #6 Understanding and Targeting Customers - Social media Data, Browser Logs, Sensor Data, Clicks, Web searches Understanding and Optimizing Business process - Logistic management, web search trends, Improving Employee performance Personal Qualification and Performance Opimization - Consider wearables, sleep monitoring apps. Improving healthcare and public health - Decode DNA Strings, Predict disease patterns Improve Sport Performance - Using video analytics to track team performance Improving Science and Research - Census Data, experimental data Optimizing machine and device performance - Self driving cars, gps data, and sensor data Improving Security and Law Enforcement - detect and prevent Cyber attack Improving and Optimizing Cities and Countries Financial Trading
- #9 Your work as a Data Scientis is a pick up any Data set and turn it into something meaningful. Combine, process and reprocess data until it says something.
- #11 This is the reason we are making the class a contributory one because we deliberately faced the reality that Data Science is not a skill you can learn all in 12 Weeks and we don’t want you to be alone after the 12 weeks. It’s all this aspet that we will try and guide you through as much as we can.