Complete Data scientist roadmap and all about data science. How to become a data scientist. What is Data science. Who is data scientist. Why Data science is the future.

1. DATA
SCIENCE
TODAY EVERYTHING IS GOING ONLINE AND AMOUNT OF
DATA IS INCREASING EVERY SECOND. SO, THE DEMAND
FOR GETTING MEANINGFUL INSIGHTS FROM THIS HUGE
AMOUNT OF DATA IS ALSO INCREASING AND THAT’S
WHY DATA SCIENCE IS THE FUTURE

2. WHAT IS DATA SCIENCE
Data science is an interdisciplinary field that uses
scientific methods, processes, algorithms and systems
to extract knowledge and insights from noisy,
structured and unstructured data, and apply knowledge
and actionable insights from data across a broad range
of application domains. Data science is a "concept to
unify statistics, data analysis, informatics, and their
related methods" in order to "understand and analyse
actual phenomena" with data. However, data science is
different from computer science and information

3. WHY DATA SCIENCE IS FUTURE
Everything is changing to digital nowadays and because
of that more and more data gonna be recorded and
maintained, so to improve the performance of any firm
we need to study data and make better business
strategies for continuous growth. So its gonna be
obvious demand of any data scientist increases to great
extent. If we look a little bit more ahead, the US Bureau
of Labor Statistics predicts that by 2026—so around six
years from now—there will be 11.5 million jobs in data
science and analytics. The estimated total pay for a

4. WHO IS A DATA SCIENTIST
Data scientists are big data wranglers, gathering and
analyzing large sets of structured and unstructured data.
A data scientist’s role combines computer science,
statistics, and mathematics. They analyze, process, and
model data then interpret the results to create actionable
plans for companies and other organizations.
Data scientists are analytical experts who utilize their
skills in both technology and social science to find trends
and manage data. They use industry knowledge,
contextual understanding, skepticism of existing

5. HOW TO BECOME DATA SCIENTIST
• Skill 1: Gain database knowledge which is required to
store and analyze data
• Skill 2: Learn statistics, probability and mathematical
analysis.
• Skill 3: Master at least one programming
language. Programming tools such as R, Python are very
important when performing analytics in data.
• Skill 4: Learn Data Wrangling which involves cleaning,
manipulating, and organizing data. Popular tools for

6. • Skill 5: Master the concepts of Machine
Learning. Providing systems with the ability to
automatically learn and improve from experience
without being explicitly programmed to.
• Skill 6: Having a working knowledge of Big Data
tools such as Apache Spark, Hadoop, Talend, and
Tableau, which are used to deal with large and complex
data which can’t be dealt with using traditional data
processing software.
• Skill 7: Develop the ability to visualize results. Data
visualization integrating different data sets and creating