Many people are familiar with machine learning from shopping on the internet and being served ads related to their purchase. This happens because recommendation engines use machine learning to personalize online ad delivery in almost real time. Beyond personalized marketing, other common machine learning use cases include fraud detection, spam filtering, network security threat detection, predictive maintenance and building news feeds.
Now lets brief about Machine Learning
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.
And, the good news is, Latest technology is advancing consistently and revolutionizing every facet of our routines. Humans had their first brush-up with Machine Learning when voice-controlled personal assistants — Amazon’s Echo and Alexa — were launched. These devices are a new normal with the trend of smart homes picking up. Driverless cars, which were a quintessential sci-fi fantasy, aren’t something of the far-off future now. These new-age vehicles, aimed at cutting down human labor, are tested across the world for their utility benefits.
Let’s dive in how Machine Learning is revolutionizing our lives.
Machine Learning can empower surgical robots to help doctors in medical procedures while ensuring minimal invasion and high precision. This achievement can improve the success rates of surgical procedures and accelerate turnaround time with cost benefits. In the context of healthcare, ML can be a critical enabler to efficient diagnosis, research, and treatment, thereby underlining the holistic transformation of the sector.
From administration, record-keeping to fully fledged diagnosis and treatments, ML has the capability to analyze the crisis at hand and compare it with numerous other scenarios for the right treatment and procedure. This comparison saves time and paves a strategic path for the decisive medical approach.
Today’s transportation industry is highly influenced by Machine Learning. The technology has been instrumental in eradicating the threat posed by reckless driving through the deployment of sensory management and automation. This has intelligized vehicles to understand the surrounding parameters and take precautionary action whenever required to ensure passenger safety.
China is testing driverless buses for its city while Google and Rolls Royce have collaborated to design and launch the world’s first self-driving ship by 2020. The ship will be leveraging Google’s Cloud Machine Learning Engine to understand the sea and objects surrounding it. This will enable the remote controlling of the vessel and end up reducing the resources involved in the transportation.
Beyond vehicles, Machine Learning can soon by deployed for traffic management and preventing traffic congestions on roads. China and Singapore, at the moment, are leading the innovation and creating algorithms that can help drivers choose routes cleared off traffic.
3. BFSI — Banking and Financial Service Industry
Several banks and financial institutions are using ML-based complex algorithms to analyze and predict loan risks and assess the quality of the application. Therefore, reinforcing them to take informed decisions. It’s also helping in the detection of frauds and scams via analytics.
The otherwise traditional industry is favoring Machine Learning to mitigate its transformational bottlenecks and create better user engagement for the stakeholders, including the customers. Voice Recognition, Chatbots, and Predictive Analysis are helping bridge the gap between financial establishments and potential customers. Today, customers can contact a business anytime around the day and rest assured of instant, real-time replies from Chatbots. This saves time as well as improves the customer experience for the organizations.
It’s true that teachers cannot be replaced by bots, but they sure can be assisted by the diversity. Machine Learning can provide to their methods of teaching and education on a whole. ML capabilities are being used to assess the child’s academic understanding, analyze the way he/she perceives knowledge, and create a customized academic plan that can help focus on the wholesome attribute of that specific student.
The algorithms analyze test results and create a unique grading system that can free up the teachers’ time and help refine the education modules for children. Not to mention, ML can be extremely helpful for students with disabilities and learning gaps.
ML, in addition to teaching, is simplifying administrative duties. It helps educational institutions create an organized means of administering students and staff via its automated responses, customized software and more. It’s all about breaking down the processes and making organizing an institution less of a burden.
Lawyers remain busy. So, automating their day-to-day activities can free them from the redundant tasks and help them focus on creating liable solutions to the cases at hand.
Machine Learning brings forth this automation and adds a new twist to the otherwise conventional industry. It augments documents and their processing. It also analyzes them for proofs and research, which can help the lawyers extract the relevant information without having to expend time in pouring over books and legal documents. They can also help systemize the operational tasks, such as staying abreast with the hearings and keeping note of the impending dates.
ML can strategize how lawyers review their cases and hopefully, can speed up the cases that otherwise take months and years to resolve.
Internet of Things (IoT) & the future
The IOT Technology isn’t coming soon It’s already here and the year 2017 is the best know for IoT to came into business effective process.
Big players are entering the game. Google bought the Nest Thermostat, Apple is coming out with Home Kit, ARM and Intel have both released new developer tools, Relayer got $2.3M in funding from Cisco to build an Internet of Things App ecosystem and Samsung announced earlier this year that they want to connect 90% of their devices by the end of 2017.
Internet of Things (IoT) is the next wave, world is going to witness. Today we live in an era of connected devices. Internet of Things is a term given to the attempt of connecting objects to the internet and also to each other – allowing people and objects themselves to analyze data from various sources in real-time and take necessary actions in an intelligent fashion.
Many big technology industries like apple, Intel, ARM, Google, IBM, and Microsoft have welcomed IoT and are putting huge investments and R&D efforts in this domain. Cisco’s Internet Business Solutions Group (IBSG) predicts 50 billion devices will be connected by 2020 and the market size, as predicted by GE is 10-20 trillion USD. The IOT Technology is the next revolution for users and brands.
As per the expert’s estimation the IoT market to expand $1.7 trillion by 2020, connecting approx 50 billion devices. The question is, from where the growth come from? Certainly, U.S. rules the forefront of technological developments, whereas China is in the middle of a massive economic expansion. Then, who will witness the IoT transformation? India to experience the IoT growth, and to become the largest consumer of IoT devices in the years to come.
As the future of IoT Technology is bright in India, businesses are more likely to take advantage of the IoT benefits. The industrial automation and efficient operations will soon take over the overall industry. For instance; Logistic is expected to enhance its operation with IoT devices. Many companies have already joined the race to maximize their transportation. Apart from this, in order to make the IoT more accessible, today some of the businesses are focusing to develop a platform’s design.
Right from the way we work and play, IoT will change everything. This IOT technology will transform and assure accuracy, efficiency, and overall productivity. Now, IoT will enable us with better equipped connected device, helping us to make smart and swift business decisions, delight our customers and predict the accurate requirement.
Whenever, innovation is introduced in the tech world, there are many challenges that will still remain the same. However, overcoming these issues, we can get a wholesome approach to success, as the future of the IoT in India is a promising, not to doubt. Visualizing the positive impact, the government is on the way to back sincere effort to develop better infrastructure. Hence different industry verticals are endeavoring to develop innovative products, and understand the benefits the Internet of Things provides.
Further, with sufficient time and resources, the IoT implementation in different business shows great and impressive result on a large scale.
Few more facts :-
1) The Internet of Things (IoT) industry is booming—in 2017, And need for IOT Developer is growing along with it.
2) Gartner predicts By 2020, more than 20.8 billion IoT devices will be in use, A recent report from vision mobile projects 4.5 million IOT Developers will be needed by 2020.
3) The term “IoT developer” remains broad, “There are a lot of discipline areas that are in play, including security, networking, systems engineering, cloud programming, and hardware device programming,” “It pays to be multilingual so that you can be flexible and play many different roles in the team.”
4) While these solutions may seem complex, the deployment of an IoT solution is simpler than would be expected for such a trans-formative benefit. With IoT technologies, you have the ability to dream big,adjusting the scope of your IoT solutions over time and with ease.
5) If you are a techie, or techie-at-heart, you’ll also enjoy his musings on the incredible rate of technological change we’ve seen in the past 50 years.
Linux Careers – The Future
Linux careers offers plenty of possibilities. At the time of this article, a simple search of ‘Linux’ on Indeed.com yields nearly 72,000 jobs with 52,000 of them being recently posted. Clearly, Linux is a space where a good, solid long term career is possible. But there are some things you should know before you decide to make the leap.
Recently I had the opportunity to sit down with two long time Linux system administrators. These pros have been in the trenches for many years and shared their expertise with me. I then took their thoughts and added it to my list of “career truths” that I was already aware of and decided to share the details here.
Who should consider Linux IT as a career?
So if you’re thinking Linux IT is a good match for you, consider the following:
- Do you enjoy learning new things? Linux IT is constantly evolving filled with wonderful discoveries and new technologies. But this isn’t a career path where you only learn about one thing and that’s it. The learning never ends.
- Are you well suited to troubleshooting? This is a key asset that I think escapes many newcomers entering any IT field. Not everything works like it should and despite your best efforts, you may be spending a significant amount of time troubleshooting why a server is crashing or one of your scripts isn’t running as it should.
- Can you do your job effectively even when stressed? This is one thing I’d love to see more Human Resource Managers (HR) ask new recruits. While there are exceptions, many areas of Linux IT is high stress. If your job involves critical data availability and/or working with stubborn end users who refuse to recognize best practices, you’re going to be stressed at times. You may need to be the type of person who can keep it together and persevere through some high stress situations.
If you can answer yes to all of the above and also have an aptitude for technology, then Linux IT may be a career path worth pursuing.
Preparing for your first Linux IT job
When you’re fresh out of College, the first temptation is to immediately start racking up various Linux and networking certifications. On the surface, this is fine. However you must pursue honing your Linux skills first.
This means learning basic Linux commands and functions to the point where you can utilize tools like sed, grep, cron, and awk. Master these, perhaps even learn a bit of shell scripting while you’re at it.
Being able to automate basic administrator tasks is actually very important and will demonstrate you’re the right person for a potential job. During your introduction to these tools, bundle this with a “Linux server” that you’re managing. I would start with this set of Linux tutorials.
Some newbies looking to pursue this career path may be tempted to immediately jump into advanced networking, visualization and container management. I advice each of those individuals to start with the links above first, master them and then move onto more advanced Linux tools and technologies.
Once you have a solid handle on your skills, I recommend making a name for yourself before seeking out your first Linux IT job. There are three common approaches to this.
- Volunteer for a local non-profit. Whether this is something as remedial as teaching people how to use computers at first, it may soon turn into your managing their data stores and other server needs. Many of these opportunities evolve into the volunteer handling a variety of duties. Linux IT is no different.
- Apply for an IT help desk position. Sometimes this means working for a local ISP or perhaps a web hosting company. Even if neither of these seem to compliment your Linux career goals on the surface, it shows future employers that you’re able to handle difficult challenges when needed. Plus, it’s not uncommon for people to be recruited for better paying Linux IT jobs from these entry level positions. I’ve personally seen it happen many times. As long as your skills are up to par, you’re in a far better position when an IT position in the same company opens up than the new kid fresh out of school is.
- Network at industry events. I’ve had younger people tell me this approach to job hunting is dated and my reply is that the hiring managers at these events would disagree. Hone your skills, make up business cards listing your skills and contact information. Then begin introducing yourself to any booth or person at Linux industry events who you happen upon. I had a ten plus year consulting job that I got taking this approach. It works.
Building your Linux career: IT job interviews
Depending on the Linux IT job type you’re seeking, odds are you’re going to be interviewed by both HR managers and IT division managers. The former is more easily fooled by an exaggerated resume than the latter.
Choosing your first Linux IT job
It’s at this point you have to decide what next steps will make the most sense for you. As a general rule, this usually is broken up into the following segments.
Location of the job. Is there a commute? Since it’s highly unlikely anyone is going to hire a junior admin to work remotely, figuring out whether to commute or relocating is the best option.
Career path direction. Is the company you’re interested in working for going to make continued learning available to you? Do they pay for certs, conferences, and training? Not all of them do and if one of them does, this needs to be something to consider as it’s a tangible asset that will advance your career. As a junior administrator, I’d go so far as to suggest that a company that pays a smaller salary but pays for continued education is the better choice when starting out.
Company culture. When you’re given a tour of the place, do you get the sense that everyone is reasonably content with being there? As cliché as this must sound, I can’t impress upon your enough how important this is. As a junior administrator, you’re going to be seeking out help and mentorship from some of these individuals. If they hate being there, odds are so will you.
Can you do the job asked of you? Remember what I said about being honest about your skills? Once hired, you’re expected to accomplish tasks that match the skills you’ve claimed to possess. Honing your skills and being in a workplace that encourages continued learning is going to present you with a very attractive Linux IT career.
Ever-evolving Linux IT
Remember what I said about your career evolving over time? That you may start out doing one thing only to shift gears and go another way? This is true when you’re starting out as a junior administrator. You may start off simply managing data stores only to move into DevOps one day. You may even feel like the skills you learn today won’t apply to your career later on if you decide to get into something a bit different.
Don’t worry, your skills are legacy assets that will only serve you as you progress through the IT ranks. By building up your basic Linux skills first, starting off in the trenches at a low level IT job, you’re learning secondary skills that will transform you into a more effective Linux IT employee.
Facebook, Google, Amazon, NASA, Tesla, even Microsoft. Linux is the operating system acting as the backbone for the world’s most powerful and innovative companies. Looking for a future proof technical skill? It’s hard to go wrong with Linux.
Enroll with us for Linux courses to gain the foundational Linux skills you need to pursue more advanced education and certification. Choose between two options, depending on your experience level. Unsure about which course is right for you? Its time you stopped and trained with us…
One of the “most sought after” domain these days is Artificial Intelligence (AI). Artificial Intelligence (AI) capabilities for e-commerce and other Platforms today are able to leverage available information regarding similarities and dissimilarities between customers, along with the Phone. The ability to utilize the vast datasets regarding customer behavior and usage patterns acquired by e-commerce platforms, artificial intelligence – with its self-learning algorithms and intelligence, creates personalized shopping experiences for online buyers.
Here’s a snapshot of how Artificial Intelligence (AI) is slowly changing the world of business and shopping for good:
The Chatbots Revolution for both, machines and smart devices
AI is rapidly reducing manual effort in communication for the e-commerce platforms via natural language processing (NLP) and machine learning capabilities, AI’s chatbots are able to automate conversation with the buyers.
This can carry out the daily transactional conversation, which otherwise required human support staff. Furthermore, the chatbot-led conversations transpire with zero scope for human error. Chat assistants are further being used for CRM, personalizing buyer experience by addressing their queries.
This is the reason why e-commerce sites are today able to drive conversations with their users via AI. The Industry Gurus believe that e-commerce players to go big on the entire chatbots revolution. Gartner predicted that chatbots are going to replace 85 per cent of customer interactions by 2020.
Virtual Buying Assistants:
These days AI-powered virtual assistants, e-commerce sites are able to provide their shoppers with a personal fashion assistant. The technology assists shoppers through personalized recommendations, on the basis of their preferences and past usage patterns. For example, sending notifications or prompts when prices drop; the virtual assistants will let the shoppers know the instant there is a price change, this will help them to increase the footfalls on the site, leading to more successful conversions.
Monotonous or Traditional merchandising systems no longer possess the required wherewithal to analyze large volumes of data, or read and predict consumer trends. This is where AI comes in, helping consumers with what to buy, based on their behavior patterns and preferences. The same also provides e-commerce sites with actionable insights to make their platform best suited for their buyers, and come up with the most relevant offers, campaigns, strategic messaging etc.
Making conversations and Improving Order Fulfillment:
Because of the sheer number of mushrooming e-commerce platforms, consumers today are bombarded with a volley of messages. It not a surprise anymore, when most of the times important communication from e-commerce sites is missed by the customers.
To tackle these challenges, Companies using Artificial Intelligence exploit, Predictive Intelligence and Contextual Messaging functionalities to determine the right time to target a customer. This ensures higher conversation rates, whilst also improving brand’s engagement with its customers.
Furthermore, the noteworthy aspect of the technology is that the practice can be used to target each and every customer individually. Companies can now re-engage with every customer via strategic messaging, most opportune time, and a communication channel of their preference which makes it convenient for them.
AI potential has been utilized by e-commerce companies across the globe to minimize shopping cart abandonment, automate processes and optimize the conversion rate. E-commerce sites are increasingly adopting AI to provide a much more personal, intuitive and simplified experience to their patrons.
The future belongs to industry-level collaborations between AI and e-commerce giants, with the sole intention of putting forth the best platform for the customers.
What is changing in the realm of big data?
Big data is changing the way people within organizations work together. It is creating a culture in which business and IT leaders must join forces to realize value from all data. Insights from big data can enable all employees to make better decisions—deepening customer engagement, optimizing operations, preventing threats and fraud, and capitalizing on new sources of revenue. But escalating demand for insights requires a fundamentally new approach to architecture, tools and practices.
Teaching tomorrow’s Data Scientists
BICARD gives you the tools, techniques, and fundamental concepts needed to make an impact as a data scientist. In just 12 weeks, you’ll apply problem-solving and creative thinking to real-world data sets, gaining experience across the data science stack: data munging, exploration, modeling, validation, visualization, and communication.
Grounded in Python, our program covers the necessary tools and concepts used by data scientists in industry, including machine learning, statistical inference, and working with data at scale. As you learn more advanced techniques, you’ll use tools like SQL and NoSQL. When you graduate, you’ll have a solid grasp of machine learning, statistics, and will have built numerous data science applications.
Week 1 – Exploratory Data Analysis and Software Engineering Best Practices
Week 2 – Statistical Inference, Bayesian Methods, A/B Testing, Multi-Armed Bandit
Week 3 – Regression, Regularization, Gradient Descent
Week 4 – Supervised Machine Learning: Classification, Validation, Ensemble Methods
Week 5 – Clustering, Topic Modeling (NMF, LDA), NLP
Week 6 – Network Analysis, Matrix Factorization, and Time Series
Week 7 – Hadoop, Hive, and MapReduce
Week 8 – Data Visualization with D3.js, Data Products, and Fraud Detection Case Study
Weeks 9-10 – Capstone Projects
Week 12 – Interview Preparation
We’ll give you a take home assignment to assess your quantitative and programming skills, then conduct two technical interviews. The first evaluates your proficiency with programming in Python while the second covers probability, statistics, experiment design, and basic modeling. We look for students who are familiar with data analysis tools and practices and a background in a quantitative disciplines like foundational statistics, probability, linear algebra, or mathematics.
What is an Embedded Systems Design?
An Embedded System as the name suggests, can be thought of as software embedded in a computer hardware system. Embedded systems are part of large and much complex systems to enhance or assist a specific function of the system or it can also be an independent system. The precise definition of an embedded system is that it is a microcontroller or microprocessor based, driven by software, real-time control system designed to carry out an explicit task. For example in latest designed cars, we have automatic transmission, anti-lock brakes, GPS navigation which are all embedded systems. Other examples include fire alarm to sense fire and then send the signal. Medical equipment, cameras, mp3 players, household appliances, airplanes, vending machines, even cellular phones and PDA all include embedded systems into them.
The three basic components of an embedded system are
- Application Software
- Real Time Operating System (RTOS)
- C and C++ programming
- Real Time Operating Systems
- Embedded Linux system design.
- Knowledge for Object Oriented Programming (OOP).
- Knowledge of the Software Development Life Cycle (SDLC).
- Knowledge of network architecture and communication protocols such as Ethernet, TCP/IP etc.
- Understanding of assembler, compiler, linker and loader.
- Understanding of source-level debugger, in-circuit emulators (ICE) and JTAG debuggers
- Understanding of tools like memory testers, Execution tracers and Coverage testers.
Electronics Skills- Basic concepts of microprocessors and electronics like memory addressing, serial ports etc. must be strong
Problem Solving Skills – Real world problem solving skills are needed skills in this domain. An embedded system engineer might spend quite some time troubleshooting an issue. Problem solving skills are thus critical.
Opportunities in Embedded Systems Designing and Programming
Embedded Systems Designing is a specialized occupation. The engineers who trains in designing and developing the systems should possess strong knowledge of electronics and programming.
PG Diploma in Embedded Systems will train and skill the engineering students further to implement modern real time embedded systems. It facilitates to acquire knowledge, skill needed to conceive, design, implement and deploy dedicated embedded systems. By this course, a student gets all the technical know-how and professional attitude to progress in the domain of embedded systems.
There is huge demand for embedded systems engineer as these systems are becoming more and more useful and important in developing and enhancing various large systems. There has been exponential increase in computing power, ubiquity of connective and the merging of various technologies have led to hardware and software systems to be embedded in everyday use systems and products.
Hence engineers in this area have excellent career and growth prospects in various kinds of industries like
- Consumer Electronics
- Manufacturing industries (medical equipment, defense etc.)
- Aerospace and other large as well as small scale industries.
They can be, depending on their skills, knowledge, aptitude and interests –
- Researcher (R&D engineer),
- Embedded Systems Engineer/Developer/Programmer
- Embedded Systems Tester
- Support Package Developer
- Protocol Development Engineer
- Embedded Systems SME (Subject Matter Expert)
Thus, training in embedded systems can provide opportunities to be a part of the leading innovation and it is the tool for the future for present generation. Embedded systems is part of IoT, which is coming age revolution.
For more information visit our website www.bicard.org
The recent development in technology is leading towards making world a intelligently hyper-connected planet.
IoT – Internet of things is a system which connects objects and devices (like coffee maker, air conditioners, washing machines, cell phones, traffic lights etc.) which are of use to people in their everyday lives at home and work. It is a concept which has the ability to influence the way we live and work. IoT concept in not limited to only people and their daily activities but also applies to different component of machines & industry. IoT not only connects objects to the Internet but also enables devices to intelligently identify and communicate with other devices, objects and even people. This will create a new system of information-sharing among people, facilitated by our devices. It will create a network of People-People, People-Things and Things-Things.
Usage of internet as well its availability is increasing and its connectivity cost is decreasing day by day. More and more devices are created with Wi-Fi and sensors and its penetration among the people is huge. Fast growth of smartphones and internet access has also lead to the concept of IoT.
According to an analyst firm, today there are 14 billion object and devices are connected to the internet and by 2020 these number of devices could be anywhere from 20 billion to 100 million.
Internet of Things is the combination of both hardware and software technologies. The hardware consists of the connected devices and the networks that link them, such as 4G, Wi-Fi and Bluetooth. Software components include data storage platforms and analytics programmes that give information to its users. When these hardware and software components are combined to provide services, real value is created for businesses, consumers and governments.
Source: www.boozallen.com – Internet_of_Things.pdf
Characteristics of IoT
CONNECTS – It connects the physical world around itself one thing to other.
COMPUTES – It processes every input it is fed and then communicates to other related devices.
COMMUNICATES – After processing, it communicated with other devices connected and each device has unique identity.
Example – There are digital signs with embedded sensors on the highway. These sensors detect black ice on the highway at certain location and send automatic messages to incoming vehicles to slow down. This prevents accidents, cuts emergency service costs and decreases overall traffic congestion.
Various other applications of IoT whether it’s in transportation, energy, health, or the military, industries are already benefiting from IoT.
Smart home – It is the highest Internet of Things application. There are lot of companies active in smart home in comparison to other applications of IoT. Various multinational corporations like Philips, Haier, or Belkin have pitched in this area.
Smart city- it includes traffic management, waste management, water distribution, urban security and environmental monitoring. IoT solutions solves many issues faced by the city related to traffic, noise, pollution, security etc. and makes city a better and safer place
And many other like Wearables, Smart grid, Connected car, Connected health, Smart retail, Smart farming and so on.
Implementing IoT-enabled systems will allow businesses and organizations to maximize existing investments, secured transmission, analyze data, and provide near-real time decision support which will change how business is done.
Bicard is a leading Institute in Pune, India which provides training in various cutting edge technologies and makes people Industry-Ready!
For more information visit our website:
BICARD at Shivaji Nagar, Pune
Office No.68-71, 4th Floor,’C’ Block, Shrinath Plaza, Dnyaneshwar Paduka Chowk
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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.
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.