We continue hearing measurements about the growth of data. For example:
• Data volume in the ventures will grow 50x year-over-year amongst now and 2020.
• The volume of business data around the world, over all organizations, copies at regular intervals.
• In 2010, Eric Schmidt broadly expressed that each 2 days, we make as much data as we did from the beginning of human progress up until 2003.
How might you utilize this data further bolstering your good fortune?
On the off chance that you need to exploit this data, you should initially start putting away it some place. In any case, how might you store and process enormous informational indexes without spending a fortune on capacity?
That is the place Hadoop becomes an integral factor.
Hadoop is an open-source programming structure for putting away and handling huge informational collections. It stores information in a disseminated mould on bunches of ware equipment and is intended to scale up effortlessly as required. Hadoop enables organizations to store and process huge measures of information without buying costly equipment.
The colossal preferred standpoint of Hadoop: It lets you gather data now and make inquiries later. You don’t have to know each inquiry you need replied before you begin utilizing Hadoop.
When you start putting away data in Hadoop, the potential outcomes are huge. Organizations over the globe are utilizing this data to take care of enormous issues, answer squeezing questions, enhance income, and the sky is the limit from there. How? Here are some genuine cases of ways different organizations are utilizing Hadoop further bolstering their good fortune. Machines produce an abundance of data–much of which goes unused. When you begin gathering that data with Hadoop, you’ll learn exactly how helpful this information can be.
Here’s another awesome illustration: One power organization joined sensor information from the shrewd matrix with a guide of the system to foresee which generators in the lattice were probably going to bomb, and how that disappointment would influence the system in general. Utilizing this data, they could respond to issues before they happened.
Do you ever ponder what clients and prospects say in regards to your organization? Is it great or awful? Simply envision how helpful that information could be in the event that you caught it.
With Hadoop, you can mine online networking discussions and make sense of what individuals consider you and your opposition. You would then be able to examine this data and settle on continuous choices to enhance client discernment.
Money related administrations organizations utilize investigation to evaluate chance, form speculation models, and make exchanging calculations; Hadoop has been utilized to help fabricate and run those applications.
Retailers utilise it to help examine organized and unstructured information to better comprehend and serve their clients.
In the benefit concentrated vitality industry Hadoop-controlled investigation is utilized for prescient support, with contribution from Internet of Things (IoT) gadgets bolstering information into huge information programs.
Media communications organizations can adjust all the previously mentioned utilize cases. For instance, they can utilize Hadoop-controlled examination to execute prescient upkeep on their foundation. Enormous information investigation can likewise design proficient system ways and prescribe ideal areas for new cell towers or other system development.
By now it is mostly common knowledge, that Big Data is essentially a large volume of information collected through myriad sources, in various formats, it is also understood that this big data has a key to all future plans and strategies that the company needs to adopt if it truly wants to succeed.
True, big data is information gathered from the internet enabled services, social media, and other similar sources. It can be typically characterised by 4 V’s…
- Volume – it is getting vast as compared to the traditional sources through which data used to be captured
- Variety – data comes from various sources, machine generated and people generated
- Velocity – the speed at which this data is being generated, it is phenomenal and never stops
- Veracity – basically the quality of data, as one has little control of the volume.
The evolution of the technology has helped organisations apply the findings, not only while strategizing but in almost every aspect of the functioning of an organisation. For internal and external benefits. Merely capturing data is not beneficial, but to understand what insights you get from that data is paramount in decision making. In the ever-evolving business environment, having historical insights is not enough, but to get accurate future predictions, using data analysis and predictive modelling and visualisation techniques is also colossally essential, mostly while developing strategies.
Big data, eliminate intuition such that all imperative decisions can be made through a structured approach, and with a data-driven insight.
To put it simply it is a broad three-step process performed in a loop. (a) Manage Data- extract relevant data (b) Perform analytics on the data – gain insights and use algorithm’s (c) Make Decisions.
Big Data can further Benefit organisations in the below mentioned 5 areas
- Comprehend market Conditions – through big data, organisations can predict what future customer behaviour will be, purchasing patterns, choices, product preferences. This will leverage the company, and help contest competitors.
- Know your Customer Better – through big data analysis, companies come to know the general thought process and feedback in advance and make course corrections. Companies can reduce complaints and act on it before it becomes big. There are big data tools that predict negative emotions, prompt action can be taken to mitigate the same by organisations.
- Control Online Reputation – Sentimental analysis can be done through Big Data Tools; thus a company can check on what is being said by whom online and manage their online image efficiently and effectively.
- Cost Saving – firstly, there might be an initial cost of application of big data tools, but in the long run, the benefits will outweigh the cost. Secondly, with the application of real-time big data tools, the IT staff will be less burdened, so these resources could be used elsewhere, and lastly, the application of big data technology will make storing of data easier and more accurate.
- Availability of Data – Through Big Data tools, relevant data can be available, in an accurate and structured format, in real time.
The value of Big Data Insights is priceless. One needs to have the patience and discipline while application of the same. Ask the right question to gain accurate insights. With the quality of data, the possibilities are great, for businesses to flourish.
It’s no longer a question whether an association needs Big Data technique. It’s an issue of how soon they grasp it. IT experts are scrambling to get certified in Big Data or Hadoop, which is relied upon to end up basically the most heated tech-expertise in the following couple of years. Huge Data is gradually receiving noticeable interest known everywhere throughout the world, as organisations overall verticals like utilities, retail, media, pharmaceuticals, vitality, and others are grasping the most current IT idea. This is also the reason why Big Data training and certifications in big data have become so popular in the recent years.
According to some current techniques, numerous association did not have the capacity to meet the requests of the client because of the unpredictability of information to break down and prepare the information. To dodge these sort of issues, Organisations are actualizing Big Data innovations. Overall areas of the world, 53% of the 1,217 organisations had embraced no less than one Big Data activity.
Why Big Data Certification?
The truth of the matter is, organisations are attempting to get Hadoop ability. Ventures embracing Hadoop need to be guaranteed that individuals they contract can deal with the petabytes of Big Data. The testament is a proof in such manner, making a man in charge of the information.
The following happen to be the benefits of big data training, especially with Hadoop:
- Taking after are a portion of the regular points of interest Big Data affirmation offers.
- HR managers and HR groups are chasing for aspirants having big data and Hadoop certifications. It’s an unequivocally preferred standpoint over those having no affirmation.
- Huge information accreditation gives an edge over different experts, in regards to the compensation bundle.
- Hadoop, as well as big data certification, helps an individual quicken vocation development amid the inside employment posting process.
- One of the real points of interest Big Data certification gives is that it is useful for those attempting to change over to Hadoop from other specialised foundations.
- Hadoop certification underwrites hands-on understanding of working with Big Data.
- Confirms that an expert knows about the most recent Hadoop highlights.
- The big data certification helps in talking all the more unquestionably about the innovation to the organisation while organising with others.
While the above are the general benefits of anyone who happens to have pursued a big data training or certification. The biggest benefit of all would most definitely be the salary packages that some of the expert Data scientists receive these days. As the world becomes increasingly data driven, organisations of various stature have begun to depend on these big data magicians, to create their magic with numbers and help their respective firm’s progress.
Now for the important question. Where does a data aspirant go to get a certification in Big Data? Imarticus Learning happen to be the best in class, especially when it comes to certification in Big data courses that are thoroughly industry endorsed.
The program includes comprehensive coverage of Big Data trends, HDFS architecture, MapReduce concepts, Query tools like Hive and Pig, data loading tools and several advanced Hadoop concepts, all taught by experienced industry professionals who have 15+ years of experience in this domain.
Our program is aligned to meet the needs of the industry and the focus is always on job-readiness rather than being excessively academic. The curriculum and learning methodology is designed and vetted by our Analytics Advisory Council which features senior management from top Analytics firms to ensure effective learning. You will also have periodic guest lectures with industry professionals to help gain new perspectives and broaden your horizon.
With big data analytics continuing to achieve prominence at a number of software services companies, its popularity is growing to unprecedented levels. As big data analytics happens to offer many perks as well as great packages, it makes for a great choice for anyone looking to pursue a fulfilling career.
Armed with certifications from Imarticus Learning, as a candidate you have millions of opportunities opened up for you. So if you are looking for a serious career change, or have plans of starting off in the data science industry, you would have a few questions. One of them being which data analytics tool should you master? The answer to this question would most certainly be either Hadoop or Python or both.
Why do you ask? Let’s talk about the reason why you must be getting certified in these two data analytics tools.
Let’s begin with Python. Due to its great similarities with tools like Java, C or Perl, the basics here are the easiest to master for the novices. As this tool happens to be very beginner friendly, a freshly graduate programmer would find it be a perfect fit. With having to write less code and other features like code readability, simple syntax, and easy implementation, it happens to be one tool that every data analytics aspirant must study.
For any programmer, the most difficult task is finding out bugs and squashing them, but in Python, its unique design lends itself really well to all of its users. Writing less code basically means that the programmers would find debugging easier and will also be prone to fewer issues as compared to other programming environments.
In addition to all the above winsome attributes, Python also happens to be an object oriented language. This would make it easier for the user to migrate to any other object oriented language, just by learning the syntax of the new language. But one of the most important reasons why you should learn Python is that it can power Google’s search engine, YouTube, Dropbox, Mozilla, NASA and IBM too.
Moving on to Hadoop, this is an open sourced software framework, which is very easily able to store and process great amounts of data. Many professionals have been blown away by its sheer horsepower. It has the ability to make a huge difference to many organizations by assisting them in their marketing needs.
It so happens that Hadoop and NoSQL are believed to be the fastest growing technological networks in the market of Data Science. There have been reports which state that Hadoop will possibly grow in the Big Data Market and reach up to $13.9 billion by the year 2017.
As Hadoop has quite a lot of implementations, professionals who have expertise in this programming language have a wide range of career roles to choose from. All one needs to have is the deep rooted understanding of how the framework of Hadoop works. As it is one of the most sought after skills, it also pays really well
Thus, here we have the most touted reasons, as to why one must study Hadoop and Python.
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There exist a number of free and accessible Python Machine Learning resources in the market today. While it may be true that anyone can begin their learning process, in a hassle free way but, the amount of variety poses a threat of confusion. Many data aspirants undergo a number of apprehensions like deciding which course to take, how to proceed and most importantly, where exactly to begin.
In order to reduce your apprehensions, we have got here a complete guide to being efficient at understanding and mastering, machine learning with Python. Let’s begin with tackling one of the most important questions, which is ‘Where to Begin?’ While everyone, regardless of the field of study they belong to, faces this question but, it would be agreed upon that to begin somewhere, is the hardest step to take. Couple that with having to make a choice from among the multiple options and you land up confused and staggering.
There are a number of professionals who code but have sufficient working knowledge about computer science. Similarly, if you are looking to get trained in Machine Learning with Python, you don’t need to have a through theoretical knowledge, the practical side more than makes up for it. There exist a number of source libraries, which help with the machine learning aspect, while working with Python. A few of them, those that are known as scientific Python libraries, can be distinguished by the names, nymph (used for N-dimensional array objects), pandas (python data analysis library), matplotlib 2D plotting library) and so on. If you are well aware of the variety of topics of machine learning, which make it easy to work with Python and with the help of professional training courses, it would be a cake walk.
Assuming that the reader is a novice at Machine Learning, Python and any data analysis resources, scientific computing or any other related resource. Let’s begin from the basics, to begin with, you are required to mandatoraly have a certain amount of foundational knowledge about Python, in order to make use of it in Machine Learning. When it comes down to it, your level of experience and comfort in the usage of this data analytics tool, would help you choose the proper starting point. To begin with, you have to first install the Python software, using one with industrial strength implementation for operating services like Linux, Windows is always better.
As most of the work of a Data Scientist revolves around Machine Learning algorithms, it as a whole reflects the field of Data Science. For an aspirant, it is not very important to thoroughly understand kernel methods, as opposed to being well versed with the practical usage of the same. Like they say, practical application of any particular tool, is entirely relative to the theoretical understanding. Machine Learning, in particular, is a concept which very few can learn on their own. This is why most people tend to opt for professional training institutes. Institutes like Imarticus Learning, usually focus on teaching various data analytics tools and machine learning, with a more practical approach coupled with case studies and mentoring from the industry experts.
Since the time its popularity hit the roofs, there’s one statement about Big Data that’s remained a constant. “It isn’t about what you know, it is mainly all about what you do, with what you now.” While this may seem as a bit of gibberish to some, industry experts claim that it happens to be a valuable lesson, that companies across the globe will soon end up learning, in the coming years, especially when it comes to the field of Big Data.
Innumerable industry experts among us claim, that 2017 will be the ‘It’ year. The year when data science and big data are bound to go mainstream. Did you know that there are a number of teenagers out there, who are entirely dependent on Google analytics to monitor their brands, regardless of their size. There are a number of parallels drawn between, the thriving start-up culture on one hand, and the increasing developments in the field of predictive analytics and target marketing.
As we are well into the year of 2017, it can be noted, that there are a number of changes in store for Data Science. There are signs of a meaningful shift, gradually taking place when it comes to business and big data. It probably would be the first time, when data analytics, would be the driver of a number of business operations. This change will be a very rewarding proposition for all of those working in the data science industry. While on the other hand, those companies who are lagging behind in this race of technology, could be in for some serious liabilities.
According to Harvard Business Review, “A majority of business outfits today, are nowhere close to recognizing the value and benefits, that data analytics can bring to their firms.” Industry experts believe there happen to be a number of reasons for the same. From lack of communication to absolute absence of a proper, well-designed plan could result into businesses, being entirely oblivious to kind of benefit data analytics can bring. While this news may lead you to panic, there are still a number of things that you, as a business entrepreneur can do and you, as a data science professional can be well aware of.
When it comes to gathering the generated data, almost every single person in the company must buy into the value analytics. If your firm fails to do so, it runs the risk of your company ending up with data, that is either worthless, or enormous amounts of data insights, which will rarely be put to use. Every company and firm out there, needs to make a proper action plan, especially when it comes to the professionals, who are responsible for managing data, reporting it, gathering information, inputting the data and most importantly, who analyzes this data. If these processes aren’t outlined properly, your data will almost never pay.
As the whole world comes to terms with the potential of Big Data and data analytics, there is an increasing need for trained professionals, who are adept in working with data analytics tools. A number of data enthusiasts have begun to look for institutes like Imarticus Learning, which will offer them industry endorsed training programs, in various data analytics tools like R, SAS, Python, Hadoop and so on.
Data Science today has become the most advanced field industry in comparison to all those industries that have existed in the market sphere. One thing that is very evident about this field is that it is ever evolving in nature. This is one of the reasons why a lot of data science experts advice professionals to forever remain on their toes when it comes to the various developments in this landscape.
Mark Twain’s famous line, “Don’t let school interfere with your education” work the very best for all the professionals in this sphere.
As the field of Data Science is fairly new, there are a number of tweaking’s, replacements, additions and newer solutions being introduced here almost on a daily basis also. This is the reason why it makes it so imperative for Data Scientists to be aware of all the newer trends. After getting certified in any one data analytics tool, keeping in touch with the various new developments in terms of other tools and functions, becomes very important for any Data Scientist, who is looking to expand and improve their career. Data Scientists are time and again advised to learn and relearn certain ‘soft-skills’, which will help them stay on top of their game when it comes to the various requirements of the industry.
While technical knowledge is of utmost importance, being able to develop certain professional traits and habits has great benefits Data Science professionals for these. It is said that learning never ends, it is a continuous process. Similarly for a data analyst, keeping up with all the market trends and trying their best to expand their skill set is a per-requisite. This is the very reason, why a number of professionals today reach out to us to help them gain knowledge of other data analytics tools like SAS Programming, R Programming, Hadoop, Python and more. It is always a better bet to add to your laurels than just resting on them. The most crucial parts of being a Data Scientist is not just to have great skills, but also be able to communicate their results very effectively. As this field has expanded from just being IT related to more fields throughout the market sphere, the same is expected out of a Data Scientist. A professional who has all the technical knowledge, but does not have any knowledge of the business perspective, would not be able to effectively deliver the results of the analytics work.
Business strategizing and development are two very important parts of data analytics and until a professional is not able to deliver on the technical as well as the business front, he becomes more of a liability than an asset to a firm. Thus reaching a balance between these two aspects will open up a candidate to huge benefits thus. Apart from working on your soft skills, working on your networking skills can also make a world of difference for all the data scientists out there. Attending a number of conferences and related events, will not only help you learn a trick or two but also will help you gauge current trends and give you a sterling CV.
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The phenomenon that is well known as Big Data Science has literally gone on to spread all over the globe in a similar fashion as that to a raging wildfire. The world of business and commerce has remained no stranger to this concept and field and in fact has embraced it more than any other. Big Data has been the catalyst in some of the most remarkable discoveries, especially in the field of HR. While the technical aspect dictates that the various valuable insights provided by big data have made for amazing growth and development of a number of firms, it has also helped a number of HR managers in targeted recruitment as well as employee enhancement. As a professional in the HR industry, regardless of the position, there are a certain number of things and concepts that one has to abide by. As surprising as it may sound, it has been proven recently that these few concepts still hold great value and importance, especially when it comes to big data in HR.
The first basic thing, that all HR professionals need to remember, is the massive difference that there is between “story telling” and “story selling”. This is basically only in the context of how a professional perceives a certain data set. It is important for these professionals to be able to distinguish between a very neutral interpretation of data and on the other hand, a data set that is used to derive a certain expected solution. This skill becomes very important in a market, where every vendor and seller is out there to promote their business solutions, entirely on the basis of data and numbers. When faced with numerous such vendors, it holds in positive stead for you to be a little skeptic.
Another basic concept here is not confusing correlation to causation, which is the one of the primary attributes of statistical analysis. This simply put in layman terms, goes on to state that just because two things are related to each other, it does not mean that they are also the cause of each other. This is very important especially in the world of Human Resources, because HR services are most often related to positive business results. This would only be possible, when the professionals are able to realize the difference between certain variables, that can actually cause similar kind of impact, thus statistically stating the connection between the various HR activities and profitability. The most basic trick to know here, is when you would not require causation at all, when only correlation would be enough to provide the required results. While these days, the data is very much required by the HR professionals, in order to determine the correlation and causation, as well as, evaluation of results and making the decisions. It is also important to know when and how the sample size, taken into account is sufficient.
Thus we can infer that HR is soon becoming the latest avenue for all the data scientists out ther to test their abilities. There is no surprise hence, in the increasing popularity of various institutes. Imarticus Learning, provides excellent professional training in a number of data analytics tools like R, SAS, Hadoop and so on.
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As the world rapidly becomes data driven today, the most exciting places which are rapidly developing as a result of this are all the startups out there. While data technologies have been around for quite a while now, various factors like the increasing speed of data generation, as well as the ability to store data, have resulted into the emergence of a number of advanced data run startups. Apart from being either involved with data analytics and being data driven, these startups are very unique in terms of their various founding members and the educational backgrounds they belong to, the industry that they work in and the opportunities available therein, the kind of investment and funds they receive or raise and so on. Apart from these deciding factors, there is also the growth factor, which makes for a great importance and good career in big data field in terms of how popular a startup goes on to be.
Here’s a list of four such amazing, Indian start-ups, which would be a dream for any Data Science aspirant, to work with.
Taking the use of data science, to enhance the HR departments of every company out there, this startup was founded in the year 2002. With data science and artificial intelligence, as its core drivers, Edge Networks, in the bid to decrease the cumbersomeness, encountered by a number of job seekers out there, has come up with their product, HIREalchemy. Their solution basically deals with talent acquisition, internal workforce optimization and talent analytics.
Gone are the days, when one would wish for a way to operate any and every electronic device, with the help of a touch screen. Now it is actually possible for anyone to control, any electronic device with a screen, just by their gestures. The best part? An Indian startup, Fluid AI is attempting to create a huge revolution, which would be really gainful for not only the government of India, but also for the Finance, Web and Marketing industries. Imagine how exciting it would be if any screen, could assist you with more efficiency than any human assistance would be able to provide.
Mad Street Den
While we all may joke around about how sometimes, online shopping can be entirely misleading. Especially when you want to buy the kind of dress that you’ve been dreaming of. You find the exact one and order it, but something entirely different is delivered to your place, which is absolutely not what you have been looking for. This is where this start-up’s flagship product, Vue.ai comes into the picture. It relies heavily on the concepts of Machine Learning and Artificial Intelligence and attempts to provide the customers, with exactly what they’ve been looking for by sending targeted emails and the likes.
India is a very large, populous nation and more often than not, a lot of doctors are faced with the herculean task of being able to provide diagnosis, as well as treatment very promptly. This is where this start up comes into the picture. It is being devised to assist various medical practitioners, in rapid diagnosis, with the help of Image Processing, Classification with AI and Machine Learning at its core.
These amazing startups make it seem like a dream, for any Data Scientist to work in the Indian Data Industry. With various institutes like Imarticus Learning, offering specialization courses in various data analytics tools like R, SAS and Hadoop, achieving the dream is very possible today.
The recent couple of years have been witness to this huge amount of buzz created all over the IT world by the concept of ‘big data’, with it more often than not being related to in the print and electronic media. One of the most phenomenal discoveries was that all the data that has been rapidly generated was stored in the entirety of the past decade. For instance, it was in the year 2000 when 25% of the world’s information was being stored in the virtual format. Cut to the current year, more than 98% of information is stored in the digital format in our daily lives. Believe it or not, today, the entire world is generated more than 30,000 gigabytes of data that is almost being generated every second of every day. When you sit to carefully think about this, the change seems to be of almost astronomical proportions. This as it would, in the progression of all things IT, has led to the creation of huge data sets and in a way there has also been the whole issue, about how and where and especially in what manner would the data be stored.
More important than that is the question of what. The answer to what of this data, more specifically the answer to what exactly can be done about this data, lies within two words: Data Scientist. These are professionals who are basically given the responsibility of extracting value out of these huge data sets, thus in a way, assisting in making valuable decisions, for the growth and development of the companies. Today there is no field left that, has not been penetrated by the. The various fields that have been developed, in terms of their efficiency and their functioning, mostly due to the presence of big data are, health, IT, finance, oil and gas and many more.
The newest addition to this ever increasing list, is the field of agriculture. The National Research Council, is of the opinion that something known as, precision agriculture can come into existence due to the introduction of big data. It basically refers to a management strategy, which will be making use of information technologies to collect data, from multiple sources in order to facilitate various quality decisions, when it comes to anything and everything related to crop production. While so far the system of precision agriculture and big data are a little different from each other, in terms of the technical aspects, there are chances of inculcating these two concepts in the near future.
Precision agriculture is still involved, with graphical representations of the field maps, wherein the main purpose is to just identify the areas which would be less nutrient deficient in order to sow seeds. As this concept already has a lot of generation of data in place, it surely will help with the process of data analytics, thus these two fields being complementary. This promises a lot of development in terms of job opportunities for all those great Data Scientists out there.
If you are planning to earn career in data science, then Imarticus Learning offer various business and data analytics courses in both online and classroom mode.