Unstructured Data, Opinions, and SAS

If you are a Twitter or Facebook user, you must be familiar with the barrage of opinions that flows in with every major or minor happening in the real world. You must be also familiar with the trend of “viral” content which may be an article, a video, an audio, an infographic, or even a single picture.

Two of the major mouthpieces of the general public and the public figures alike, Twitter and Facebook are two platforms where people come out to voice themselves on any issue that matters to them. Twitter has 288 million active monthly users and counting while Facebook has 1.35 billion and up. Perhaps even imagining the data that these two create is difficult. And these are just two of the popular social media platforms, we are not even talking about the likes of Instagram, Pinterest, Linkedin, Google+, and more.

So, what happens to all the data that is created at these places? Does it just get swallowed up into the endless chasm of virtual reality? Is it just useless after a new day on the timeline begins?

Well, although the amount of data is humongous (that’s why it’s called Big Data), it is certainly not useless. At least not for business organizations, think tanks, research organizations, government agencies and anyone else for whom keeping a track of public opinion, and public actions is important.

For businesses, the tweets, posts, blogs, customer reviews, comments and similar inputs that build up unstructured data is a goldmine waiting to be exploited. This textual data is actually the way to understanding public sentiment about a particular product, service, or event that they have offered and use this sentiment to make future business decisions to improve operations and performance.

If you are a public figure, say a politician, it is possible to know how many people across the world support the statement you made last night in that event, and that will tell you whether your ideology connects with people or if they going to blast you if you continue going down the same path.

The text mining and analytics tools offered by SAS give the power to collect unstructured data and prepare it for analysis, to gain insights and actionable instructions. In light of the expansive and fastidious need of analytics in almost every domain, it has become imperative for professionals looking forward to make a leap in their career to undergo training regarding such tools and obtain relevant certifications.

AnalytixLabs, the institute that has been voted among the top 5 institutes for analytics training in India, is here to complete just that requirement. To know more about our courses and training structures, visit our website https://www.analytixlabs.co.in/.

Emergence of Big Data Systems and Hadoop

To better understand the market drivers related to Big Data, it is helpful to first understand some past history of data stores and the kinds of repositories and tools that were used to manage these data stores. Most organizations analyzed structured data in rows and columns and used relational databases and data warehouses to manage large stores of enterprise information. The preceding decade saw a proliferation of different kinds of data sources — mainly productivity and publishing tools such as content management repositories and networked attached storage systems — to manage this kind of information, and the data began to increase in size and started to be measured at petabyte scales.

In the 2010s, the information that organizations try to handle has broadened to include many other kinds of data. In this era, everyone and everything is leaving a digital footprint. Organizations and data collectors are realizing that the data they can gather from individuals contains intrinsic value and, as a result, a new economy is coming forth.

As this new digital economic system continues to develop, the market sees the introduction of data vendors and data cleaners that use crowd sourcing to test the outcomes of machine learning techniques. Other vendors offer added value by repackaging open source tools in a simpler way and bringing the tools to market. Marketers such as Cloudera, Hortonworks, and Pivotal have provided this value-add for the open source framework Hadoop. It represents another example of Big Data innovation on the IT infrastructure.

Apache Hadoop is an open source framework that allows companies to process vast amounts of information in a highly parallelized way. It is an ideal technical framework for many Big Data projects, which rely on large or unwieldy datasets with unconventional data structures. One of the main benefits of Hadoop is that it employs a distributed file system, meaning it can use a distributed cluster of servers and commodity hardware to process large amounts of data.

Some of the most common examples of Hadoop implementations are in the social media space, where Hadoop can manage transactions, give textual updates, and develop social graphs among millions of users. Twitter and Facebook generates monolithic amounts of unstructured data and use Hadoop and its ecosystem of tools to manage this large amount of data.

Big Data comes from myriad sources, including social media, sensors, the Internet of Things, video surveillance, and many sources of data that may not have been considered data even a few years ago. As businesses struggle to keep up with changing market requirements, some companies are finding creative ways to apply Big Data to their growing business needs and increasingly complex problems. As organizations evolve their processes and see the opportunities that Big Data can provide, they try to move beyond traditional BI activities, such as using data to populate reports and dashboards, and move toward Data Science-driven projects that attempt to answer more open-ended and complex questions.

We at Analytix Labs offer Business Analytics training and a variety of other programs, such as SAS+ Business analytics, SAS Edge, Advanced SPSS and big data hadoop training for individuals, corporates, colleges and universities. Visit our website for details.

What exactly is Big Data?

Data is created constantly, and at an ever-increasing rate. Mobile phones, social media, medical imaging technologies — all these and more create new data, and that must be stored somewhere for various purposes. Devices and sensors automatically generate diagnostic information that are needed and kept in real time. Merely keeping up with this huge influx of data is difficult, but substantially more challenging is analyzing vast amounts of it, especially when it does not conform to traditional notions of data structure, to identify meaningful patterns and extract useful information. 

Although the volume of Big Data tends to attract the most attention; generally the variety and velocity of the data provide a more apt definition of Big Data. Big Data is sometimes described as having 3 Vs: volume, variety, and velocity. Due to its quantity and structure, Big Data can’t be expeditiously examined using only traditional methods. Big Data problems require new tools and technologies to store, manage, and actually benefit the business. These new tools and technologies need to enable creation, manipulation, and management of large datasets and the storage environments that house them.

However, these challenges of the data flood present the opportunity to transform business, government, science, and everyday life.  For example, in 2012 Facebook users posted 700 status updates per second worldwide, which can be leveraged to deduce latent interests or political views of users and show relevant ads. Facebook can also construct social graphs to analyze which users are connected to each other as an interconnected network. In March 2013, Facebook released a new feature called “Graph Search,” enabling users and developers to search social graphs for people with same kind of interest, people and shared locations.

Big Data is the data whose scale, distribution, diversity, and timeliness demands the use of new technical analytics and architectures to alter, enable, and unlock new insights sources of business value. Social media and genetic sequencing are among the fastest-growing sources of Big Data and examples of untraditional sources of data being used for analysis.

Big Data can come in multiple forms, including structured and non-structured formats such as financial data, text files, multimedia files, and genetic mappings. Contrary to much of the traditional data analysis performed by organizations, popular varieties of Big Data are either semi-structured or unstructured in nature, which requires a lot of engineering effort and tools to process it and analyze the same. Environments like distributed computing and parallel processing architectures that enable the parallelized data ingest and analysis the preferred approach to process such complex data.

Exploiting the opportunities that Big Data presents requires new data architectures, including analytic sandboxes, new ways of working, and people with new skill sets. These drivers are causing organizations to set up analytic sandboxes and build Data Science teams. Although some organizations are fortunate to have skilled data scientists, most are not, because there is a growing talent gap that makes finding and hiring data scientists in a timely manner difficult. Still, organizations such as those in web retail, health care, genomics, new IT infrastructures, and social media are beginning to take advantage of Big Data and apply it in creative and novel ways.

If you want to get big data certification then you can visit AnalytixLabs, a premier training institute for analytics, big data, hadoop training and more.

What’s in Store for Data Scientists in 2015?

Since data science and big data are dynamic, fast-paced domains that are constantly evolving, the year 2015 has some goodies up its back as well as some dampeners.

There are quite a handful of things expected this year, with one of them being Hadoop getting translated into more production uses as companies look to utilize dark data sitting inside Hadoop systems that have already been used to derive values. There will be some unique apps that will be specialists in specific uses. Markets are going to be savvy about data transformation, horizontal analytical platforms enabling, features creation, operationalization, and model development. And as a result, the rush for hiring data scientists is going to continue.

Big data technologies will be broadening their horizons, and data science innovations will be dazzling board rooms and campuses alike. As businesses, educational institutes, as well as philanthropists acknowledge the importance of big data and data science in producing valuable insights in every domain, data literacy will be given ample focus to produce qualified professionals who can process insane amounts on data for the betterment of profit-based organizations as well philanthropic avenues like disaster relief. Clearly, data science courses are going to be much sought after.

Enterprises across domains like healthcare, energy, heavy industry, and education will realize the need of sharing data sources and are likely to lower their shields to bring together data assets and facilitate meaningful insights that will benefit the industry as a whole. Open data will be the new powerhouse.

As far as big data is concerned, it is common perception that any data is good as long it is huge. But there will be a conscious shift across industries where the game will now be data that’s connected to value. However, ethical data harnessing may be shamed by some who are not prepared to use the proper safeguards associated with utilizing data science and may end up losing in front of competitors who have thoughtful technical mechanisms in place.

Data scientists in 2015 are likely to see their skills more valuable than ever. For instance, this year may see companies transferring the key to the lockers for IT related purchases from chief information officers to chief data scientists. Moreover, there are expected to be in-house data scientists for individual departments rather than data scientists cloistering together in a separate department.


If you want to enroll yourself for big data analytics training then you can visit AnalytixLabs, a premier training institute for analytics, big data, hadoop training and more.

Data analytics: The Sexiest Job of 21st Century

Reports from CNBC and Harvard Business Review say that the sexiest job of the 21st century is that of a data analyst/ data scientist. And that’s why, it comes as no surprise that the IITian affair with finance jobs seems to be losing its sheen as more and more IIT graduates are opting for a career in data analytics, also referred as business analytics.

In broad terms, data analytics refers to the process that inspects, cleans, transforms, and models data in order to churn out meaningful conclusions that support decision-making. Analytics professionals have huge prospects as industries are rapidly discovering the benefits that Big Data can throw up. Studies have shown that the expenditure by companies on Big Data would be around $34 billion in 2020. As of the present, the biggest investors using this technology to gain competitive advantage are IT, BFSI, retail, FMCG, and consulting firms. In India, BOFA Corp., American Express, Amazon, Genpact, Accenture and HSBC are some of the highest paying companies in the data analysis domain.

Why is Big Data and analytics such a hot topic?

1. Big Data has the potential to reveal crucial information about customer behavior and thinking patterns, which can be used for strategy building and promotional marketing. For example, the likes of “recommendation engines” that companies like Amazon use to recommend particular products to a user based on his or her history also throw up unusual relations between customer practices – according to Harvard magazine, credit card companies have found that people who purchase anti-snuff pads for their furniture are very likely to make their payments.
2. The scope of Big Data revelations isn’t limited to business. Social research is also making important discoveries about human patterns. For instance, predicting the situations where crime is most likely to be committed will give leverage to police patrolling and crime control.

As more and more scientists are jumping into the Big Data bandwagon, analytics is only going to be more sophisticated in the future. Experts can safely expect to see multiple opportunities for their skills.

Who can become a data analyst?

Most employers seek candidates with at least a bachelor’s degree in information technology, statistics, computer science, business management or management information systems. The requisite skill set includes analytical and mathematical skills, with some exposure to databases, data warehousing, and data manipulation.

As of the present, there is a huge demand for trained professionals but a severe shortage of candidates with the requisite skills. The salaries for data analysts are easily more than 50% better than any other profile. Many recruiters complain that because of this burgeoning demand, individuals have clinched a hefty increase in their pay packages just by the virtue of surface knowledge about the subject.

Therefore, if you are looking at adding a valuable skill to your abilities, or if you are on the brink of deciding a rewarding career path, the world of data analytics has much in store for you.

AnalytixLabs is a premier institute in Gurgaon, India that provides some of the best courses in data analytics. Its world-class training expertise is possible because of talented and experienced faculty members who know the inside out of data technologies that will shape upcoming trends in the Indian job market. Programs are available for students as well as corporate professionals. To know more visit https://www.analytixlabs.co.in/.

Best Institutes For Analytics Courses In India

Due to the increase in the competition in the market, most of the Companies are collecting data in a faster and easier manner and in great volumes then ever before, by giving managers and executives measurable insights that can turn into a better and smarter decision making. As a result, the need for SAS trainig insitiutes, big data online training institutes has never been higher. 


Executives across companies in India have been complaining about the “lack of analytics talent” in the country and have admitted that finding trained analytics workforce is literally a nightmare. Looking at this huge supply side gap, various training companies have stepped up to train professionals in analytics so as to bridge the gap and make available trained and employable analytics professionals.

To help you choose, we’ve listed the top 10 companies, as rated by Analytics India Magazine (AIM). [Information courtesy: www.analyticsindiamag.com]:

1. Jigsaw Academy
   
2. International School of Engineering, Hyderabad
   
3. AnalytixLabs
   
4. Edvancer Eduventures
   
5. Academy for Decision Science & Analytics
   
6. Analytics Training Institute
   
7. Ureach Solutions
   
8. NI Analytics
   
9. Business Analytics
   
10. Big Data Training

All the above companies have been rated based on their course ware, faculty, infrastructure and placements.

If you wish to seek further information on the analytics courses provided by us, in India, check out our insights for the professionals analytics courses and Hadoop courses.

Business Analytics Course – A Promising Profession in Today's Scenario

Do you wish to have a promising career, a job that only advances, a profession where you are challenged, receive better opportunities and a chance of growth? If your answer is a yes, then Business analytics is the way to go. Since more and more organizations require better skills, technologies and practices to delve into past performances and deriving current strategies to drive the company, you can benefit greatly from a course in business analytics course.


A promising profession in today’s scenario, business analytics provides you the opportunity to grow and develop. The field, which is closely related to marketing, finance, credit and risk, supplying, telecommunications and transportation can help you in understanding different strategies for organizational growth, ensuring that the overall productivity of your organization increases. And with business analytics courses available online, you wouldn’t even have to worry about taking out extra time from your schedule or over training yourself.

 

Take an online course in Business Analytics to grow your career opportunities

A good business analytics course online will provide you a more promising career. It will cover basics such as relevance of the course, future of analytics and fundamental statistics. The course will also help you understand the importance of factor analysis, market segmentation and cluster analysis so that you are more responsive to the client’s need, resulting in better product management and production strategies. Credit risk modeling and time series forecasting are also a major part of the program, ensuring that you develop absolute theoretical and practical knowledge of strategizing and implementation of strategies for organizational development.

We at Analytix Labs offer Business Analytics training and a variety of other programs, such as SAS+ Business analytics, SAS Edge, Advanced SPSS and Big Data for individuals, corporates, colleges and universities. Visit our website for details.