Big Data has been growing in sectors including IT and non-IT sectors incredibly.
Have you ever admired how many data bytes are used every day? If you actually know the exact amount, it will really be mind-boggling.
According to Forbes, in the last two years, the world generated 90% of the data. It is no surprise for the technologists as the advent of new updates gets into the act of increased data usage. Forbes states that around 2.5 quintillion bytes of data have been created each day at our current pace. Hence, it is no doubt that Big Data is going to be the rule for the future enterprise realm.
Big Data helps the businesses and enterprises to move their data into fingertips more effectively than before. The reason for moving their data is to improve the enterprise’s operation, to sharpen the target audience, and to drive the personalization through different venues and sites. Big Data has started bringing big changes to corporate companies. Moreover, companies have indulged in training their employees in the Big Data realm thereby increasing the revenue and ending up on improving the client experience.
Reasons Why Every Business Should Train Their Employees In Big Data
Big Data is actually a complex field. According to eWEEK’s publisher, QuinStreet, 77% of the respondents consider Big Data as the most priority in the U.S business realm. Compared to 2014, Big Data jobs has been increased by 106% in 2017. In the upcoming years, both the Big Data companies and the employees are going to catch the crown. In addition, the number of people availing for Big Data training has also increased. Going into detail, what companies actually get when they train employees in the big domain field.
There are plethoras of reasons behind the corporate training given to the employees on behalf of the companies’ request. Here are the reasons enlisted to spray light on the importance of Big Data.
Big Data – A great money saver
Starting from big organizations to smaller ones, the Big Data renders its benefits tirelessly. According to the report published by Dresner Advisory Services, telecommunications and financial services are the leading industries that ought to adopt Big Data technologies.
Thereby, the telecommunication sector contributes about 87% of Big Data adoption whereas the financial sector contributes about 76% of Big Data adoption.
Many vendors have been adapting to the new technological change in order to establish the equilibrium between the supply and the demand for Big Data technologies.
Using Big Data also reduces the implementation of multiple staff for the same work. The biggest selling point is that Big Data technology allows companies to stay ahead of the bleeding edge on the technological cliff. Thereby, when the companies find their employees lagging in the Big Data technology, without any time lag they intrude in conducting the corporate training program. The need for corporate training is high as the companies consider Big Data as a growing profitable monster.
Big Data – Allows the path of right decision making
Most of the companies fail to succeed due to wrong decisions. Even suboptimal decisions also lead to the same case. Big Data analytics helps in allowing the organization to use the new sources. Companies use Big Data in three ways in the decision making realm.
Way 1 – Enterprises use real-time data to improve customer engagement
In today’s metrics, customer service is one of the mandatory areas in an organization. In order to offer one-on-one personalized services and solutions, companies use real-time data. According to Accenture’s survey, 92% of executives are satisfied with the Big Data results. In addition, 89% of them have at least one Big Data project in their enterprise. Even Kroger claims that the companies are getting incremental revenue over $12 billion on implementing Big Data. Hence, the company wishes to be in a profitable state by using Big Data technologies at varied projects.
Way 2 – Increased operational efficiency
Gone are the days where companies roll upon lesser data. Nowadays, companies have started leveraging data into multiple automation processes. It includes automation, strategy sale and thereby enhancing the overall efficiency of their business. Even Tesla’s vehicles have embedded sensors to collect data to improve the car’s performance. Tesla’s autopilot software is also an example of the successful usage of Big Data in enterprises.
Way 3 – Increases capacity without investing extra money
Companies that ought to use Big Data technology increased their productivity and capacity without investing any money. For instance, Sprint, a telecommunication company used Big Data analytics to reduce network errors and improve customer experience. Consistently, the brand achieves around a 90% increase in its delivery rate.
Big Data – A technology with increased stability and performance
If a company’s data has been stored in a dedicated data center, then the need to protect them becomes high. Thus the decision-makers can get benefited from their data collection without worrying about the stability and the security threats.
At the same time, Big Data also provides you with an out picture of your business. Due to Big Data’s increased stability, central banks have taken interested in Big Data.
As per the recent Big Data in the central bank’s report, 61% of the responders have been considering Big Data as a valid and auxiliary input for a successful enterprise. Compared to the current days, the move of Big Data is going to be more useful.
This is the reason why corporate training gives its importance over to Big Data as an additional shield to make successful projects.
In addition, Big Data enables you to give definite information and explanation of uninterpreted ones. According to Gartner Survey among its closed circles, around 15% of the companies deploy Big Data in corporate projects.
Big Data – A great risk minimizer
Companies using Big Data have low chances to fail through wrong decisions. As Big Data has been based upon customer behaviors, market trends, and business performance, a reflection in unexpected areas adds up the advantage.
If you are an employee finding ways to improve the decision making within the company, no matter just indulge in the best Big Data training classes. It is one of the wisest things to do now. To step in Big Data training, it is necessary to know who is eligible to undertake Big Data training.
Who needs Big Data training?
According to the 2018 training report, employees have received 46.7 training hours per year, whereas last year’s training hours were 47.6. Compared to the large companies, small companies ought to give the most hours of training with the highest average number of hours as 81.8. In the Big Data realm, every graduate can undergo Big Data training. There is no hard and fast rule to become Big Data professionals.
Big Data has a high volume of both structured and unstructured data. The data can be used by any sector in order to accomplish their goals. Added to Big Data, Hadoop is another software framework that helps in storing the data and processing it to get miserable results. Here are the Big Data job profiles that help in detailing the heading.
Job profiles for graduates after Big Data training
- Chief data officer
- Big Data Engineer
- Data Analyst
- Big Data Researcher
- Big Data Visualizer
- Big Data Solution Architect
- Hadoop Tester
- Hadoop Architect
- Hadoop Developer
- Hadoop Analyst
- Hadoop Administrator
Here comes the salary chart to depict the salary range on the basis of titles.
Big Data Job Salary – USD
Big Data Job Salary – INR
Compared to the present day, Big Data is on its way to change the technological role in many sectors. So it is wise to indulge in effective training sessions. Not only employees, but the company must also pre-plan their employee’s training under Big Data.
What skills does employee learn from Big Data training?
Big Data training from an experienced institute might help the learner to master the concepts of Big Data and Hadoop framework concepts. It also helps in knowing the deployment in a cluster environment. In addition, there are certain enlisted factors that come up as an informative source for the learner.
- Learners can understand the different components associated with the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark.
- Learners can understand Hadoop Distributed File System (HDFS) and YARN architecture and it helps in storage and resource management.
- It helps in understanding MapReduce and its advanced concepts.
- Training ingests data using Sqoop and Flume.
- Big Data training creates a database and tables in the Hive and Impala. It helps in understanding different types of file formats using Arvo with Hive and Sqoop and Schema evolution
- Training helps in making the learner understand flume, Flume architecture, sources, flume sinks, and flume configurations.
- Gain in-depth knowledge about parallel processing in Spark and Spark RDD optimization techniques.
Through Big Data training, the above said factors are an added advantage to the Big Data learner. Anyone can become a Big Data expert by undergoing the certificates enlisted below.
- IBM Certified Data Architect
- Collabera Big Data and Hadoop Developer
- CCA Spark and Hadoop Developer Exam
- IBM Certified Data Engineer
- Cloudera Certified Administrator for Apache Hadoop
- Hadoop Administration
- CCP Data Scientist
- CCP Data Engineer
After getting a clear picture of the Big Data training, know what are the top companies that ought to use Big Data in their projects.
Importance of Big Data in the corporate
Do you know why these top companies have been undertaking Big Data projects? If there is one thing that is too big to ignore, it is the massive data usage and the reason behind its influenced analytics and technology. Every year the usage of Big Data has been enhancing. Big Data gets divided into three divisions of Big Data Analytics namely, Prescriptive Analytics, Predictive Analytics, and Descriptive Analytics. Here we are taking four perspectives to explain why Big Data is important today.
Data analytics includes advanced techniques and tools from the data obtained from various resources. These data will be at different sizes. Every company improves its strategy by keeping the customer’s focus in mind. Many Big Data analytics professionals improve the gross of the company through their talent in Big Data. In addition, Big Data analytics tools reduce storage costs. What else needed? This, in turn, leads to quick decision making thereby saving energy and time.
Not only in a particular sector, but the plethora of sectors also holds Big Data scope in varied levels. Multiple industries have been using Big Data technology in recent days. In the future, it is hopefully going to increase. Few industries that ought to indulge in increased usage of Big Data are enlisted below,
Compared to the other fields, the banking field uses an enormous amount of Big Data technology. So, we came to know that Big Data has been and will be holding a unique and irreplaceable place in the near future.
What about the job opportunities for employees?
Professionals who ought to carry Big Data analytic skills are in huge demand. If you are one such professional, tap your shoulder. You are going to have a promising career in future days. Learn the analytics tools of Big Data that are used in different industrial domains. In every field, analytics is an emerging tool. You can go ahead with varying job roles as mentioned earlier in the blog. Hence, Big Data without any doubt become a wise career option too.
How and why choose Big Data and Hadoop training?
Now you are clear that Big Data definitely helps in career and business growth. But, what if a person without a Big Data background does? If this is your question, you can indulge in the institute to undergo Big Data training sessions.
There, you might get to know the actual Big Data concepts. If you are a working Big Data professional, no problem, you can also take these sessions to upgrade your talent in the same domain.
According to Indeed.com, data scientist’s average salary is $123,000 per annum. In addition, Glassdoor’s survey claims that the average salary for Data Scientist is $113,436 per annum. Pretty cool, isn’t it?
Around 44% of the job opportunities were created in this domain since 2017. Yes, you heard it right. 44%!! Added to the data science field, e-commerce and healthcare field has also been emerging in the field.
So, Big Data is slowly becoming a great giant in every industry. What as a corporate organization, you need to do? It is very simple. Just train your employees in the Big Data domain after a fine analysis of different training institutes. Here comes the little description that elaborates on the framework involved in choosing the right Big Data training modules.
Ask these questions to Google and get your research well done.
- Which tools to learn?
- What are the techniques to focus on?
- How to learn?
- Where to learn?
After finalizing the answers for all those questions, you may get a clear picture of the Big Data training and its further scopes.
Which tool to learn?
Tools? It depends upon the individual whose keen of interest differs in random. Here, we have bought out levels of tools to make the reader understand easily. Here comes the Level 0.
Let us assume you are a fresher with excel knowledge. Then, your first step is to make yourself ready to play with Pivot tables in excel to make simple data manipulations and apply lookups.
The next phase is to choose either SAS/R/ Python. You can choose any one of these languages. Surf and compare three languages and go for the best. The comparison of three languages helps you to choose the right language.
Add your repository to one of these visualization tools also. Add either QlikView/ Tableau/D3.js.
The next level is choosing Big Data tools. The Big Data tools go itself into multiple levels starting with Hadoop stack – HDFS, HBase, Pig, Hive, Spark. You can also go ahead with the most popular NoSQL databases like MongoDB.
Finally, there are few exceptions to keep in mind. If you are from the MIS/reporting background, then you can start level 2 first and then go to level 1. On the contrary, if you are from software background/web development with notable knowledge in Java or Python, then jump to Level 3 directly.
What are the techniques to focus on?
After deciding the tools, the next comes the techniques. When you are clear with the tools, then the technique part is very easy to narrate. Here come the techniques under Big Data.
- Statistics basics
- Basic predictive modeling
- Machine learning tools
- Neural nets and deep learning
These are the levels of techniques you ought to choose. Go one by one and never skip the technique levels.
How to learn?
Learning methods and circumstances clash each other. Actually, learning depends on two factors. They are,
- Resources spent on learning
- Self-learning motivation
On one extreme, you may have the option of self-learning. But, do you think self-learning really helps in delivering the concept? I didn’t hope so. I have recently read an article by Will Estrad from Rasmussen.
He stated that still classroom sort of learning is what liked by most of the employees and students who wish to have face-to-face interaction. Even online classes go well when you have the chance to know the full experience details about the professor. Few employees are ready to undergo online courses which at the end goes in knowledge vain.
For companies, it is always the on-campus training that they trust. It is a well and good option to conduct corporate classes on their premises to know how well their employees are interacting with their trainers. At the same time, fine research is also a vital factor in deciding the right training institute.
Where to learn?
At last, we are the final point but a crucial point. We have heard companies saying that searching for a good and experienced institution is a daunting task. Do you really think it is daunting? No, it is not that much difficult. When your filtering is good, you can land at an experienced institution in no time.