LinkedIn is a business-oriented social networking service, which was founded in December 2002 and is mainly serves as professional networking. LinkedIn has been using Big Data to develop following product offerings-
1. People You May Know
This feature of LinkedIn reminds the users with the suggestions about other users present at LinkedIn who wish they might probably connect. Most of the LinkedIn data is offline and moves at a very slow pace. Through this feature, “People You May Know”, LinkedIn pre-computes the data by recording 120 Bn relationships per day in a Hadoop MapReduce pipeline, which is running 82 Hadoop jobs that are in need of 16TB of intermediate data. The data infrastructure uses bloom filters for accelerating join operations while running the jobs that provide 10 times better performance. There are 5 test algorithms producing an approximate data of 700 GB of output data, “People You May Know”
2. Skill Endorsements
Skill endorsements is a product used by the recruiters in order to look for the skills and endorsements of a particular candidate. A member can endorse any other member in their network, for a skill displayed on the profile of the endorsed person. Skill endorsement is a deep information extraction data problem. The workflow determines the various skills that exist for a member. The skills are then joined with the profile of a member, social graph, groups and other activity that can help in determining the skills for the person.
3. Jobs You May Be Interested In
LinkedIn uses various Machine Learning and Text Analysis algorithms for showing relevant jobs on a LinkedIn member’s profile.The textual content such as skills, experience and industry are extracted from user’s profile and similar features are extracted from the job listings on LinkedIn. A logistic regression is run for knowing the ranking of relevant jobs for a particular member based on the extracted set of features.
4. News Feed Updates
LinkedIn incorporates data analytics and intelligence for understanding what kind of information the user wishes to read, what subjects he might be interested in and all other types of updates.
Thus, with this kind of data-driven strategy, LinkedIn has continued its growth exponentially in terms of its revenue and member base through innovative data products
The global Big Data Market has accounted for an increase from $42 billion in the year 2018, and is expected to reach $103 billion in the year 2027 at a CAGR of 10.48% during the forecasted period. The Big Data market is growing at a CAGR of 10.48% With the increase in number of mobile devices and apps, the growth of big data solutions enhancing the organizational return on investment are some of the factors that complement the market growth. Factors such as lack of awareness of benefits of big data solutions and services as well as the privacy and security concerns in big data hinder the market.
Big Data not only refers to the data itself, hut also the set of technologies that capture, store, manage and analyse large and variable collections of data in order to solve the complex problems. Big Data solutions have enabled the organizations to effectively manage the large data volumes thereby reducing costs.
Scenario of Big Data in Today’s World?
Today, organizations big or small have realized the importance of data and the impact that it can bring to the organizations. The firms are regularly re-investing in Big Data and the allied technologies for making informed decisions. It begins right from optimization of supply chain systems and workflow management to enhancement of customer experience.
Some Interesting Statistics on Big Data
- It is predicted that by 2020, the amount of data present will rise to 40 zettabytes
- 90% of all the data has been created in the last two years
- In the year 2012, only 0.5% of data was analysed
- Today, Internet generates about 2.5 quintillion bytes of data every day
- 97.2% of the organizations are heavily investing in big data and AI
What are Some Future Trends in Big Data?
Some of the trends that are going to rule in the future under Big Data includes the following-
i. Dark Data
Dark data simply refers to the data that is generated from the non-digital sources and digital data has always been undermined by the value that it holds. The data sets are usually untapped, unstructured and untagged and may also be referred as dusty data. In future, such kind of data sets are about come into limelight and will revolutionize this industry
Privacy continues to be one of the major shortcomings in today’s time. We, users of data barely have any idea regarding how the data generated by us, is going to be used and shared amongst the firms and the Big Data Hadoop, is expected to constantly be on the rise. New policies have and will be introduced in context of data consumption and analytics, by paving a way for a safer ecosystem where consumers generate data
iii. Data on the Rise
The Big Data Hadoop future is always on the rise and the amount of data generated per day will also continue to grow. In today’s time, the amount of data generated per day is 2.3 trillion gigabytes of data and will continue to rise ever. The presence of smartwatches, smart TVs and smart wearables present in the market are continuously collecting user data
How Does Big Data Integrate with Other Technologies?
Technologies such as Artificial Intelligence, Machine Learning, Blockchain etc. are marking their impressions today in our everyday lives. Today, there are devices that “talk” to each other over a connected network and share and generate the data that is being fed by the user. There are algorithms learning patterns to process the information from the generated data. The simplest example of Internet of Things or IoT can be the smart TV present in the household, connected to the user’s home network and generating data based on the user viewing patterns, interests and more. The social media applications installed, are also considering the personal tastes and preferences and cumulatively working on the user persona for better delivery of the online content and streaming options.
- The combined market of Big Data and Hadoop is projected to grow from $17.1 Bn to $99.31 Bn by 2022 with a CAGR of 28.5%
- The Big Data applications and analytics is expected to grow from $5.3 Bn in 2018 to $19.4 Bn in 2026 with a CAGR of 15.49%
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