1. Real-Life Challenges of Big Data

2. Learning Objectives • Acceptance of big data • Confusing variety of big data technologies • Big data on-premises vs. in-cloud costs • Complexity of managing data quality • Data from diverse sources • Unreliable data • Dangerous big data security issues • Recruiting and retaining big data talent • Troubles of upscaling • Conclusion

3. What is Big Data Big data - refers to the big clusters of data that is generated every day by millions of people all across the globe. It has provided many benefits to the companies who use it as a tool to understand their data and take conscious business decisions based on it. It is an evolving field and has got some real challenges too.

5. Challenge #1 Insufficient understanding and acceptance of big data • Organizations neglect to know even the very basics of Big Data Advantage • Clear comprehension • Organizations may burn through bunches of time and assets on things

6. Challenge #2 Confusing variety of big data technologies • Do you need Spark or would the paces of Hadoop MapReduce be sufficient? • Is it better to store information in Cassandra or HBase? • Finding appropriate responses can be precarious.

7. Challenge #3 Expenses - Big data on-premises vs. in-cloud costs • You'll need to mind the expenses of new equipment, new contracts, power, etc. • you'll have to pay for the advancement, arrangement, setup, and support of new programming. • If you settle on a cloud-based huge information arrangement, regardless you'll have to contact staff (as above) and pay for cloud administrations

8. Challenge #4 • Data from diverse sources - At some point or another, you'll keep running into the issue of data integration, since the data you have to investigate originates from assorted sources in a wide range of configurations. • E.g. web-based business organizations need to break down information from site logs • call-focuses, contenders' site 'sweeps' and online life. • Information configurations will contrast • Unreliable data - No one is concealing the fact that big data isn't 100% exact. And with everything taken into account, it isn't so damaging either. The fact remains is that you never know when is it exactly and when it is with faults. It is likely to contain wrong data and duplicate copy of itself. • big data isn't 100% exact • contain logical inconsistencies too • It's far-fetched that information of a very second-rate quality can bring any helpful bits of knowledge to your business.

9. Challenge #5 Dangerous big data security issues • Security difficulties of big data is seriously a huge issue that merits an entire other article committed to this theme. • Big data selection tasks put security off till later stages • The multiple times big data security just gets thrown away.

10. Challenge #6 Recruiting and retaining big data talent • Big Data Salary (Annual) • big data analyst: $135,000 and $196,000 • data scientist’s: $116,000 to $163, $ 500 • business intelligence analysts: $118,000 to $138,750 • Manageability Deficiencies • Many are expanding their financial limits and their enrolment and maintenance endeavors • they are offering all the more training chances to their present staff and for the individuals • numerous associations are looking for innovation

11. Challenge #7 Troubles of upscaling • The most common component of big data is its dramatic capacity to develop • Your solution's structure might be thoroughly considered and acclimated to upscaling with no additional endeavors. • The genuine issue isn't the real procedure of presenting new handling and storage limits.

12. Conclusion • Understanding those challenges give an upper hand • Study these challenges well and see that you do not fall prey to any one of them • Experience the technology, tool, or process

13. Thank you Happy learning