IoT and Big Data are two sides of a coin. IoT systems will be streaming lots of data in heterogeneous forms which will have to be managed by the organisation. It is the biggest challenge which the organization will face. Thus, it is quite clear that both IoT and Big Data technologies will have to be used together to realize its full potential.
IoT will provide the important and interesting data, for e.g. data from sensors and actuators, but just the data collection is not enough. For better outputs, these data has to be studied, interpreted, analysed and insights has to be derived for better functioning of the IoT devices as well as business functions.
With IoT, one of the foremost things to be concerned of is huge, continuous stream of data coming into organization’s data storage. Hence the data centres must be prepared to handle this supplementary load of heterogeneous data and the companies will have to adapt technologies which can be mapped with IoT data.
After upgrading the data centres to match with IoT systems, proper analytics platform should be put in place. The actions to be taken on IoT data are different than any other data streaming. These actions are correlated to events and based on metric calculations. Hence analytics solutions for managing the IoT data will be done keeping in mind these actions.
The various examples of IoT and Big Data –
- Transportation industry – It places sensors in their vehicle to track them and a closer eye on them but more importantly, it provides data like on – fuel efficiency, delivery routes and time given by drivers. This information is useful in making the transportation more efficient and productive by optimization.
- Manufacturing – They place IoT sensors to machines and collect important data about the equipment which gives them clear idea about the performance, whether maintenance is required and if yes then when by which machine breakdown or the accidents can be avoided. Even by timely repairs based on the feedback data given by sensors, business end up saving money from accidental bigger expense.
- The most common example is wearable. For an e.g. fitness band gives us lot of data of current fitness routine and how our body is responding to it, accordingly we can change our fitness routine.
Thus internet of things and big data go hand in hand. Tremendous growth is going parallel in both the fields and both rely on success of each other. As more and more IoT systems are put in place and more and more data is generated and hence IoT and big data will be more and more entwined.
Every business is a data business, and in a connected world everything is an IoT device. – Hortonworks
BICARD Institute is the leading institute in India providing training and services in IoT and Big Data Analytics
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Big Data and Hadoop professionals are in huge demand. On any job portal, if one searches for jobs in data analytics and Hadoop, the results will be large which shows that the professionals with these skills are in great demand. Professionals, who are already working in the similar areas or are trying to get a better opportunity, are looking forward to add the skills of Hadoop, Data Analytics and Data Science. To fulfill this need for the professionals, there are various training and certification programs for them to achieve. Apache Hadoop foundation does not provide any certification; hence professionals are confused which certification will be useful and which are the right skills to go ahead in their career. On the other hand, the organisations do not have enough idea about what kind of professionals or which skill-sets and certifications are required for the jobs related to Big Data and Analytics.
Hadoop is a part of Data Science. Data Science is not only science but also an art. Hadoop is part of technical knowledge required to extract and process data, but along with it, it is an art to identify various new sources from where data can be extracted, the innovative ways to process and report them. Hence Hadoop project does not follow the established process but it does things which have not been done before. So, one need to learn Hadoop well.
Certifications in Hadoop
There are number of tutorials on Hadoop and its technologies on Apache Hadoop website. They do not give any certifications or approve of any certification programs. But the Hadoop Distribution Vendors give certifications as well as training and testing. Let us see what all training and certification they provide –
- CCA – Cloudera Certified Associate
- CCP – Cloudera Certified Professional
Previously, Cloudera gave Cloudera Certified Developer for Apache Hadoop (CCDH) and Cloudera Certified Specialist for Apache Hbase (CCSHB) certifications. But recently, as Apache Spark has increased its spread and immersion into Cloudera ecosystem, it is the basic reason for replacing the certificates and Cloudera considers that they will focus on performance based certifications. Hence professionals should take up CCA and CCP programs instead of CCDH and CCSHB.
- CCA (Cloudera Certified Associate) Spark and Hadoop Developer – Tests basic skills and develops the base for candidate to get trained and expertise under CCP program.
CCA Spark and Hadoop Developer exam requires you to write code and prove your skills in Scala and Python and run it on a cluster. This certification requires renewal after 2 years.
- CCA Data Analyst – A CCA Data Analyst has proven their core analyst skills to load, transform, and model Hadoop data in order to define relationships and extract meaningful results from the raw input. – As described on Cloudera site.
- CCAH (Cloudera Certified Administrator for Hadoop) – Individuals who earn CCAH have demonstrated the core systems administrator skills sought by companies and organizations deploying Apache Hadoop
- CCP (Cloudera Certified Professional) Data Engineer– focuses on how to build the “pipelines” to produce data sets that are optimized for different types of workloads. CCP Data Engineers possesses the skills to develop reliable, autonomous, scalable data pipelines that result in optimized data sets for a variety of workloads
- CCP Data Scientist-Teaches how to develop production-ready, scalable solutions.
Taking the lead in development training in Hadoop, the CCP is for data scientists to demonstrate their ability to design and develop scalable big data production environments. Candidates are required to pass two exams, a written exam and a real-world practicum. Named one of the top five big data certifications, CCP Data Scientists have demonstrated the skills of an elite group of specialists working with big data. Candidates must prove their abilities under real-world conditions, designing and developing a production-ready data science solution that is peer-evaluated for its accuracy, scalability, and robustness
HDP Certified Developer (HDPCD) – for Hadoop developers using frameworks like Pig, Hive, Sqoop and Flume.
HDP Certified Administrator (HDPCA) – for administrators who deploy and manage Hadoop clusters.
HDP Certified Java Developer (HDPCD: Java) – for developers who design, develop and architect Hadoop-based solutions written in the Java programming language.
HDP Certified Java Developer (HDPCD: Spark) – or developers responsible for developing Spark Core and Spark SQL applications in Scala or Python.
HDP Certified Associate (HDPCA) – for an entry point and fundamental skills required to progress to the higher levels of the Hortonworks certification program.
Hortonworks certifications are exclusively hands on, performance-based exams that require you to complete prescribed tasks. Hortonworks Certified Professionals have proven competency and big data expertise.
Hortonworks also offers self-paced as well as classroom training designed for developers, systems administrators, and data analysts.
With the MapR Hadoop certification programs, you can demonstrate your big data expertise and gain recognition for one of the most sought after skills in technology today. A MapR Hadoop certification proves you have demonstrated proficiency as a Hadoop Administrator, Developer, and Data Analyst.
MCCA – The MapR Certified Cluster Administrator is designed for Engineers and Administrators who are responsible for preparing the cluster for installing, setting up, and maintaining a MapR Cluster. The certification tests your ability to use MapR tools and Linux commands to set up the cluster, install, maintain, and troubleshoot common problems.
MCHD – MapR certified Hadoop Developer certification exam measures the specific technical knowledge, skills and abilities required to design and develop MapReduce programs in Java. This exam covers writing MapReduce programs, using MapReduce API, managing, monitoring and testing MapReduce programs and workflows.
MCHBD – MapR certified Hbase Developer certification exam measures and validates the technical knowledge, skills and abilities required to write HBase programs using HBase as a distributed NoSQL data store. This exam covers HBase architecture, data model, APIs, schema design, performance tuning, bulk-loading of data, and storing complex data structures.
MCSD – MapR certified Spark Developer certification exam is designed to gain knowledge and expertise for Engineers, Programmers, and Developers who prepare and process large amounts of data using Spark. The certification tests your ability to use Spark in a production environment, where coding knowledge is tested.
Soon MapR is coming with MapR Certified Hadoop Data Analyst (MCHDA)
Attaining this certification level signifies a high level of expertise for the data analyst. In addition it also offers numerous on-demand courses and other resources.
Career Benefits of Getting Certified
The role of data scientist and analysts is to leverage the heterogeneous data and deduce valuable information to fuel data driven business decisions and lead to competitive dominance. For this purpose, a certification gives you an extra edge over the entire talented pool, as you possess the real-time competence to perform operation in a faster, smarter and optimized manner.
The certification helps students and professionals to –
- Get highlighted by big companies as well as the up-and-coming start-ups in all sectors.
- Staying updated with the recent trends and emerging techniques of handling raw & heterogeneous data, drawing inferences and designing solutions at scale for clients.
- Professionals and students’ resume gets a higher value in the job market and can compensate for jobs on their terms of salary, location and appraisals, regardless of their work experience and job responsibilities.
- Gives confidence to the organization that the professionals selected for the related job will deliver best results as they have sound knowledge through certifications and they will not have to invest in training their employees.
- Certified professionals get access to resources in Big Data field.
IoT is the coming major technological revolution. The world has been progressively getting completely connected for years now and IoT is due to become a reality. To make IoT a huge success, professionals with the right skill sets will be required to design, implement, manage and execute. As of now there is a dearth of talent in this field. For this purpose let us go through top skills which are required as IoT professionals –
The skills can be divided into three areas –
Knowledge of Embedded Systems
It is the most needed skill set for IoT. This is because, the ‘Things’ in ‘Internet of Things’ refers to the devices with embedded systems. These devices are basically electronic or the electromechanical devices having computational ability to measure using sensors and then transmit the signals accordingly from these sensors. For these purpose these devices have the embedded systems inbuilt in them which are connected to the web and communicates with other devices as well as humans.
Thus, in order to get into IoT field, in order to develop an embedded system, it is extremely important to have knowledge of
- Embedded systems design
- Fabrication technologies
- Measurement systems
- Devices’ and machines’ hardware knowledge
In order to make the device or the sensors to communicate with each other and to enable the data transfer among them, embedded systems have embedded softwares. Hence for the IoT professionals, it is crucial to know the various programming languages in order to code the softwares. The various languages which are required are –
- C and C++ – These are the most common and essential programming languages required for the embedded software coding.
- Java – It is object-oriented language and it’s strong feature is its portability and flexibility similar to C and C++.
- Python – It used because of its remarkable feature of using in web development. For IoT, this language is very useful because of its ease in readability.
Networking is an important skill required for IoT, as all the devices are to be interconnected. For this purpose hardware and networking skills will be required in this area like Wi-Fi connectivity, Bluetooth, etc.
Auto CAD is the design software which is used widely for the engineering applications. Lots of design activities will have to done and it will be dynamic, so skilled Auto CAD professionals will be required to cater this dynamism.
Big Data & Machine Learning
IoT devices will generate high volumes of data and skills related to Big Data will be required to manage this heterogeneous data. In addition to managing, skills like analysing and interpreting the data will be of crucial importance in order to improve the IoT device functioning. Hence those who have these skills in addition to basic skill related to IoT will have an extra edge in this field.
In addition to managing and interpreting the data, one of the most important aspects is the security of these huge amounts of data. Security needs to be given utmost importance as data always carries sensitive information. Thus, IoT professional requires skills related to cyber security.
Display of the objects or devices in IoT systems will be much needed to have it more user-friendly and audience appealing. For this purpose, user interface (UI) and user experience (UX) design skills will play interesting part.
Internet is accessed now from anywhere from mostly all the mobile gadgets like smart phones, wearable, tablets etc. So, communications with IoT devices are going to happen through the use of mobile technologies via various mobile applications. Hence it will be an added advantage to have knowledge, experience and skills related mobile technologies, application & development.
It is already mentioned that IoT devices will be generating huge and heterogeneous data, which will require robust systems for storage. Cloud services will be highly demanded to store and manage this excessive data. Thus, there will be demand for the computing technologies professionals.
Soft skills are required in any profession to be successful and get growing in the respective field. IoT field though technical, demands soft skills like –
Communication and Presentation skills– In order to present your ideas effectively and or manage them with confidence these skills are highly required.
Collaboration – Ability to work in a team with people with different expertise is highly crucial. IoT projects includes professional with all the skills mentioned above hence it is required to work effectively in a team and produce results.
IT is a highly lucrative career field giving ample of opportunities to engineers but it is highly dynamic industry as well where the professionals need to continuously update their skill sets and knowledge. This is because of the ever changing trends in technology leading to tough competition in the IT job market. For those professionals who know the latest trends, learn new skills and stay abreast with all the changes in technology and implementation methods, for them it is highly rewarding career. With Big Data being the latest advancement, Hadoop is THE technology to master in today’s trend. Hadoop Technology has paid increasing payments since it surges business consciousness and wide enterprise adoption. As companies are yet struggling to completely understand what Big Data is, Hadoop professionals are high in demand, in fact there is a talent crunch in this area and organizations are willing to pay heavy pay for right, well trained and competitive people.
In India, Big Data and Hadoop demand is anticipated to grow five times in next few years which will generate excellent job prospects for professionals with big data skills in the analytics sector.
Future demand and job market for Big Data Hadoop skills in India –
According to The Hindu – By end of 2018, India alone will face a shortage of close to 2 Lac Data Scientists.
In last 15 years, India has secured the position of world’s largest IT outsourcing destination. For Big Data Market also India promises the same by the maths and statistics savvy engineers.
The below image illustrates the growth opportunities for big data professionals across various cities in India-
source: Image Credit- allanalytics.com
According to the above graph, Bangalore is emerging as a major global hub for Hadoop professionals in various domains like
- Banking- ICICI, Axis, Kotak Mahindra, HDFC, YES bank
- E-commerce – Jabong, Snapdeal, Flipkart, Shoppers Stop
- Telecom- Idea Cellular, Bharti Airtel and
- Automobile- Mahindra & Mahindra, Tata Motors
All the companies are adopting analytics to gain competitive advantage. This growing skill of Hadoop in India is also seizing the attention of various Multi-National Companies.
Most of the major IT giants like Flipkart, Facebook, Jabong, or Snapdeal are using Hadoop for analyzing zetabytes of data created by their million customer base every second. Hence mastering Hadoop skills will be leading the professionals to the next big dream frontier in India. Big data companies in India are staking big on IT professionals who can expand the value of their competitive plans by leveraging big data analytics competently. IT professionals can MAKE BIG in this inflating world of Big Data in India by gaining expertise in Hadoop and other big data technologies.
Bicard – The leading Training Institute in India provides various courses from 6 months to 20 hours programmes. For more information visit our website and our institute at Pune or Bhilai.
Companies and organizations generate lots of data as their business grows. But are they able to derive the insights? Or get the useful information from the data which can be useful to their business?
Business Analytics is the study which facilitates organizations derives insights based on statistical algorithms and technologies. It facilitates to prepare predictive models, to apply optimization techniques and reporting the results to customers and businesses.
BA does the iterative, methodical exploratory analysis of the organization’s data. Its main purpose is to help take data driven decisions and not based on any judgements. Hence, data of any organization is their asset and it is preferable that they leverage it for their advantage. The historical data is explored, analysed, the past business trends are identified. With the help of statistical analysis, data mining and quantitative analysis on the results from the historical and current data, the predictive models for the future are created. These models are run iteratively to get the most optimized one, which will help companies to take nearly accurate decisions.
The success of business analytics depend on the quality of data, skill of the analysts, their analytical capabilities, understanding of the technologies and most importantly the commitments of the organization towards data-driven decision making.
In short, following steps are conducted:
- Data mining (explores data to find new patterns and relationships)
- Statistical analysis and quantitative analysis to explain why certain results occur
- Test previous decisions using multivariate testing
- Create & apply predictive modelling and predictive analytics to forecast future results
What does BA do?
Orientation – Future
Answers the question – Why did it happen? Will it happen again? What will happen if we change a parameter?
Methods includes – Statistical/Quantitative Analysis, Data Mining, Predictive Modelling, Multivariate Testing
Business Analytics provides support for companies to make proactive tactical decisions, and in order to support real-time responses, it makes it possible to automate decision making also.
Types of analytics
- Decision analytics: supports human decisions with visual analytics and the user models to reflect reasoning.
- Descriptive analytics: gains insight from historical data with reporting, scorecards, clustering etc.
- Predictive analytics: employs predictive modelling using statistical and machine learning techniques
- Prescriptive analytics: recommends decisions using optimization and simulation
To summarise Business Analytics is the amalgamation of skills, technologies, applications and processes which are implemented by organizations to gain insight in to their business based on historical and current data and statistics to drive business planning.
Business analytics is vital in today’s scenario for remaining competitive and achieving success. When you get BA best practices in place, organization will benefit from data-driven decision making.
For more information visit our website and blogs on www.bicard.org
IoT can be defined as interplay for software, telecom and electronic hardware industry and promises to offer tremendous opportunities for many industries – Ministry of Electronics and Information Technology
What is IoT?
It is ground-breaking recent technology and has the potential to drastically change and improve our personal lives, our work place and our industry and manufacturing setups. It will change in terms of capabilities and efficiency. It means that any physical devices which are embedded with electronic softwares, sensors, actuators and network connectivity will be interconnected with each other. In short, it is the inter networking of the smart devices. For examples, smart homes, smart cities and smart management. Smart home for example is complete controlled automation of all the domestic devices like lightning, A/Cs, Heaters, Ventilators, Washers, Dryers, Microwaves, Coffeemakers and Refrigerators etc. with the help of Wi-Fi for remote control.
Is IoT going to revolutionize the society?
Yes definitely. For e.g. on a cold winter evening, you can set your house temperature at normal while returning back from the office. There are number of day to day activities, which we not able to do remotely can be automatically set and done. Similarly it can be done for the workplaces and manufacturing units.
How will IoT improve the competence?
When this level of remote automation is brought into system, it definitely leads to highly level of efficiency, better processes and better life.
How will IoT help common man?
Advantages of IoT application can be for individuals, businesses and including government. The domains are
Healthcare- All the patients’ record can be easily available across hospitals and that will make diagnosis and treatment faster when there is easy access of patient’s history.
Security- Facial recognition, bio metric fingerprints and detecting crimes by remote sensors, the perpetrators are detected and arrested early. In addition, highly volatile areas can be continuously monitored remotely and necessary action can be taken promptly. This kind of system setup reduces dangers, saves time and money.
Domestic-On domestic front, locks can be accessed with smartphones as the key; one can easily lock and unlock doors remotely.
Tracking everyday item consumption in the home can also be done easily and accordingly the order is placed as soon the stock levels go down. In this regard households’ consumption patterns can be known and accordingly with the use of analytics product companies can target their consumers for their advertising and marketing, which will facilitate highly concentrated marketing.
It is expected that by 2020, there will be 50 billion smart devices interconnected to each other. Hence it has started creating huge opportunity in IT as well as other industry sectors to get ready for the change.
More and more companies are going forward to develop IoT technologies and along with it many start-ups will be venturing into Iot area as there are huge bright developments excepted in this domain. Hence lot of job opportunities will be developed in the field of IoT.
For more information visit our website www.bicard.org
Business Intelligence is the broad set of tools, applications and techniques that provide organizations the visibility into complete business operations. It gathers data from internal as well as external sources, performs the analysis by running queries and then present the reports, spread sheets, visualisations, dashboards for the for the decision makers as well as functional people.
The main purpose of the business intelligence is to provide support for the Data-Driven Business Decision Making. It is also referred to as Decision Support Systems (DSS). It includes technologies and applications like Data Warehouses, Executing Information Systems and Online Analytical Processing (OLAP).
Bringing together all the data from the heterogeneous sources and integrating and creating a Data Warehouse it is called Data-warehousing. It is the core of an organization’s business intelligence system and is facilitated by the ETL tools.
The functions of data Warehousing tools and utilities are
- Data Extraction
- Data Cleaning
- Data Transformation
- Data Refreshing
Data visualization is presenting or reporting the information in a visually appealing method which helps understand the necessary details from the data in a better, faster and absorbing way. It involves selecting the most relevant and most appropriate infographics/chart/graph/reporting style for the management and executive dashboards keeping in mind the nature of the data, report to be made and the audience. More the dashboards are appealing and communicative, better the information sharing.
Business Intelligence is an approach which is similar to a rear-view. It answers the questions like
- What Happened?
- When did it happen?
- Who made it happen?
- How and When did it happen?
Based on these questions, the organisation work to derive answers and further do the analytical study part.
Benefits of Business Intelligence:
- Management Processes are enhanced.
- Business operations processes are also enhanced.
- Planning, controlling, measuring and/or applying changes that results in increased revenues and reduced costs.
- Intelligent prediction of future.
- It empowers the organization with
- Quick and efficient process requests
- Quick response to any change in organization
- Efficient Information sharing
- Improvise reporting system
- Delivery of relevant information to both local and remote personnel
Data Warehousing and BI is one of the very important modules in the entire course of Data Science. There is lot of demand for the people in this field as the amount of data has been increased hugely. More and more Big Data technologies are being adopted by the various companies and hence knowledge of BI tools and concept of data warehousing are imperative to work with Big Data.
Bicard offers in-depth Data warehousing and BI course for the experienced professionals as well as fresh graduates. It is Also an integral part of 6 months PG Diploma programme in Big Data Analytics & Machine Learning.
What is Hadoop?
It is a word which is used very often nowadays in the IT as well as some other industry sectors. It is often used in connection with Big Data. But very few know how it is related to Big Data.
Big data is the voluminous heterogeneous data in terabytes and Hadoop is a framework (not a single technology or a product) to process efficiently Big Data. Hadoop is a part of an Ecosystem to handle big data which comprises of various other supporting technologies and products.
Hadoop is an Apache open source framework written in java which has the potential to manage thousands of terabytes of data. It has quickly developed as basis for big data processing tasks like statistical analytics, business planning and processing huge volumes of data from sensors including IoT sensors. Hadoop is designed to scale up from single server to thousands of machines, each offering local computation and storage.
The main four modules of Hadoop Framework
- Hadoop Distributed File System (HDFS) – A distributed file system which is capable of storing data across thousands of servers and provides access to application data.
- Hadoop Yet Another Resource Negotiator (YARN) – A framework for resource management and schedule jobs across the clusters holding data.
- Hadoop Map Reduce- It is a parallel processing system which is YARN based and maps the data and reduces to a result.
- Hadoop Common- They are the Java libraries and utilities supporting other modules.
The other softwares which are part of the Hadoop Ecosystem
- Apache Flume– It is meant for Data Movement. It streams logs into Hadoop. It is a reliable & distributed service to efficiently collect, aggregate and move large amounts of streaming data into HDFS
- Apache Hive-It is a Data Warehouse Infrastructure on top of Hadoop for providing summaries, query and analysis. It allows SQL programmer to SQL type of statements in HQL
- Apache Pig-It is a high level platform for creating program on Hadoop to analyze large data sets.
- Apache Hbase– It is an open source, non-relational, column oriented database management system which runs on top of HDFS. It is written in Java and modeled after Google’s Big Table.
- Apache Spark-It is a powerful open source which uses its standalone cluster mode and can run not only on Hadoop Yarn but also on Apache Mesos and Cloud.
- Apache Zookeeper, Apache Oozie, Apache Sqoop, Cloudera Impala and few others.
Advantages of Hadoop
- It is scalable
- Hadoop framework allows the user to quickly write and test distributed systems and utilizes the underlying parallelism of the CPU cores.
- Hadoop does not rely on hardware to provide fault-tolerance and high availability (FTHA), rather Hadoop library itself has been designed to detect and handle failures at the application layer.