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BIG DATA by Mind Map: BIG DATA

1. Definition

1.1. The term “Big Data” refers to the collection of all this data and our ability to use it to our advantage across a wide range of areas, including business. (Bernard Marr, 2019)

1.2. Big data is a set of techniques and technologies that require new forms of integration to uncover large hidden values from large datasets that are diverse, complex, and of a massive scale.

1.3. Big data refers to the large, diverse sets of information that grow at ever-increasing rates.

2. Characteristics

2.1. Volum

2.2. Velocity

2.3. Variety

3. Practices and Applications

3.1. Banking and Securities

3.2. Communications,Media and Entertainment

3.3. Manufacturing and Natural Resources

3.4. Insurance

3.5. Retail and Wholesale Trade

3.6. Energy and Utilities

3.7. Gorvernment

3.8. Transportation

3.9. Education

3.10. Healthcare Provides

4. Benefits

4.1. Educational Sector

4.1.1. Improve Student Result

4.1.2. Customize Programs

4.1.3. Reduce Dropouts

4.1.4. Targeted International Recruiting

4.2. Business Sector

4.2.1. Better Decision-Making

4.2.2. IIncreased Productivity

4.2.3. Improved Customer Service

4.2.4. Reduce Costs

4.2.5. Fraud Detection

4.2.6. Increased Agility (Alertness)

4.2.7. Greater Innovation

5. Disadvantages

5.1. Need for Talent

5.2. Data Quality

5.3. Cybersecurity Risks

5.4. Rapid Change

5.5. Hardware Needs

5.6. Difficulty Integrating Legacy Systems

5.7. Compliance (Agreement)

5.8. Costs

6. Big Data Tools and Technologies

6.1. Hadoop

6.1.1. The High-availability distributed object-oriented platform, popularly known as Hadoop, is a software framework that evaluates structured and unstructured data.

6.2. MongoDB

6.2.1. MongoDB is a general purpose, document-based, distributed database built for modern application developers and for the cloud era.

6.3. Hive

6.3.1. Data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL.

6.4. Data Lakes

6.4.1. Data lakes are particularly attractive when enterprises want to store data but aren't yet sure how they might use it.

6.4.2. Data lakes are particularly attractive when enterprises want to store data but aren't yet sure how they might use it.

7. INTERNET OF THINGS (IoT)

7.1. Definition

7.1.1. A network of physical objects.

7.1.2. Cloud Computing

7.1.3. Future internet

7.1.4. Big data

7.1.5. Eobotics

7.1.6. Semantic technologies

7.2. Charatceristics

7.2.1. Enormous Scale

7.2.2. Safety

7.2.3. Sensing

7.2.4. Intelliigence

7.3. Trends iin IoT

7.3.1. Businesses will get serious about IoT

7.3.2. Devices will become more vocal

7.3.3. More computing moving to the edge

7.4. Practice and Application of IoT

7.4.1. Infrastructure Management

7.4.2. Manufacturing

7.4.3. Meical and Health Care

7.4.4. Home automation

7.4.5. Education

7.4.6. Energy management

7.4.7. Media, Entertainment

7.4.8. Agriculture

7.4.9. Security