Introduction of big data and analytics
Big data refers to the large volume of structured and unstructured data that businesses receive daily. It has three key aspects - volume, variety, and velocity. Big data is important for making good use of data, benefiting from cloud storage capabilities, enabling data visualization, and finding new business opportunities. It can lead to improved efficiency, sales, costs, customer service, and products/services. Common software used for big data includes Hadoop, Pig, and Hive. Challenges include finding useful information, data silos, inaccurate data, and a lack of skilled workers. Potential application areas are analytics, integration, cleaning, and updating data. The future of big data involves addressing privacy, security, latency, and scaling issues with
Introduction of big data and analytics
- 2. • Big Data Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. • Key Aspects of Big Data • Volume (Terabytes, Records, Transaction, Tables, Files) • Variety ( Structured, Unstructured, Semi structured) • Velocity ( Batch, Near Time, Real Time, Streams) BIG DATA
- 3. WHY BIG DATA IMPORTANT Making Good Use of the Data. Benefit From Speed, Capacity and Scalability of Cloud Storage. Data Visualization Organization Can Find New Business Opportunities.
- 4. Big Data can lead to efficiency improvements, increased sales, lower costs, better customer service, and/or improved products and services. Using information technology (IT) logs to improve IT troubleshooting and security breach detection, speed, effectiveness, and future occurrence prevention. Cont...
- 6. SOFTWARE USED IN BIG DATA Hadoop Open source, Java-based programming framework Design Clusters Map Reduce Powerful Model for Parallelism Based on Rigid Procedural Structure Pig Procedural Data-Flow Language Used by Programmers and Researchers. Hive Declarative SQLish Language Used by Analysts for Generating Reports.
- 7. CHALLENGES OF BIG DATA Finding the Signal in the Noise Data Silos Inaccurate Data Technology Moves Too Fast Lack of Skilled Workers
- 8. FUNCTIONS OF BIG DATA Get Value From Data Data Integration Key Clean and Maintain Data Remove Duplicates Verify New Data Update Data Implement Consistent Data Entry
- 9. APPLICATION AREAS OF BIG DATA
- 10. FUTURE SCOPE OF BIG DATA The Connectivity Internet in the Cloud Raises a Range of Privacy and Security Concerns. On the Technical Front, New Algorithms and Methods are Needed to Cope With Time-Varying Network Latency and Quality-of-Service. New Algorithms are Also Needed that Scale to the Size of Big Data, Which Often Contain Dirty Data that Requires New Approaches to Clean Effectively.
- 11. CONCLUSIONS Big data allows organizations to create highly specific segmentations and to tailor products and services precisely to meet those needs. This approach is well-known in marketing and risk management but can be revolutionary elsewhere.