Emergers

Big data and Hadoop Training Institutes

              

Systems of today handle unstructured data coming from hundreds of sources, and that’s exactly the state of art we are discussing. Plus, the business intelligence tools you’d purchased in 2016 had definitely been ecosystem-adjusted, mature for flexible deployment, and accessible to non-savvy beginners rather than managers and professionals. And yes – that’s exactly how small companies like it served! Numerous hadoop training institutes in Bangalore are equipping themselves to nurture and guide the manpower required to take the technology to the next level Big data and Hadoop Training Institutes in Bangalore.
A requirement five times that number for jobs with the need for data management and interpretation skills. International Data Corporation (IDC) predicts a need by 2018 for 181,000 people with deep analytical skills, and a requirement five times that number for jobs with the need for data management and interpretation skills. But with proper professionals can scale net heights and organizations can benefit from their competencies. The Services that we provide are,
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Emergers

Big data trends for the future

              

In a new survey conducted by Syncsort, 250 prominent respondents including data architects, IT managers, developers, business intelligence/data analysts, and data scientists weigh in on big data trends to watch in the future. Two-thirds of those surveyed work in companies with over $100 million in annual revenue. Industries represented are financial services, healthcare, government, and retail. The big trend is the move away from Hadoop experimentation into full production with big data analytics.
The future big three trends are:
Apache Spark production deployments
Conversion from other platforms to Hadoop
Leveraging Hadoop for advanced use cases
The uptick in Apache Spark is a bit of a surprise at a full 70 percent of respondents stating that Spark is the platform that they're most interested in. MapReduce came in at a distant second at 55 percent. However, Syncsort's big data analysts predict that MapReduce will remain the primary compute framework for production deployments. But the numbers tell a different story. With 70 percent of the respondents expressing a keen interest in Apache Spark, MapReduce deployments may in fact reduce over the next twelve months.
People are often hung up on the volume aspect of big data but other factors can be just as telling in the issues they raise for business. The two primary factors in this interest in Spark is that it is easy to deploy and its speed. Because Spark runs in memory, it requires big iron. Its speed also highlights one of MapReduce's biggest problems: its high-latency, batch-mode response.
But like the Syncsort experts, I believe that people will hang onto MapReduce for a while longer. The conversion or offload from expensive platforms to open source Hadoop is a significant shift. The old mainstays of mainframe and the enterprise data warehouse are becoming too expensive to deal with when cheaper alternatives are screaming for attention. The respondents agree to the tune of 63 percent stating that Hadoop will help them increase business and IT agility. Fifty-five percent expect to increase operational efficiency and reduce costs. And 51 percent want to use Hadoop to make more data available to business users. Numerous hadoop training institutes in Bangalore are equipping themselves to nurture and guide the manpower required to take the technology to the next level.
More than half the respondents view Hadoop as a way to innovate by using social media data and data from IoT sources. Oddly, only 4.9 percent reported interest in advanced use cases involving mobile apps and software. The various bigdata and hadoop training institutes in Bangalore can assist in building the workforce which is needed.


Emergers

Lack of Big Data professionals

              

Big data is a big deal. The sheer quantity of data generated over just the last few years far exceeds the entirety of the previously accumulated human historical data record. Moreover, recent reports on an estimate that the digital universe will reach 40 zettabytes (45 trillion gigabytes) by the end of the decade, a 50-fold growth.
However, as few experts around the globe point out, it’s not the amount of data that makes it a really big deal, it’s the ability to actually do something with it. Assuming, that is, you can harness not only the computational power, but the data analytics professionals required to sift through the “immensity of stuff” to uncover the relationships meaningful to your business and your customers.
According to a 2015 MIT Sloan Management Review, 40 percent of the companies surveyed were struggling to find and retain the data analytics talent. And the picture is starting to look even bleaker. International Data Corporation (IDC) predicts a need by 2018 for 181,000 people with deep analytical skills, and a requirement five times that number for jobs with the need for data management and interpretation skills.
Given the explosive growth on the help-wanted boards for data analytics experts and the intensifying competition to fill more jobs than there are qualified people, what can your company do to attract and retain talent?
Deloitte’s Analytics Trends 2016 report notes that while there is a rising number of university analytics and data science programs (more than 100 just in the U.S.), they nonetheless can’t crank out enough sufficiently trained people to meet demand. Consequently, the report recommends that companies should:
Actively recruit on campuses with data analytics programs. Develop internships and student projects both as a recruiting tool and as a way to groom students for an efficient transition to the general business world and company culture. Establish meaningful and rewarding career paths with an infrastructure in place most likely to interest and attract new talent. Consider that a Bain study of more than 400 companies with revenues in excess of $1 billion found that about a third lack the state-of-the-art tools, quality data, processes, and incentives likely to attract data-savvy professionals.
One can say that this similar dearth can be seen in the silicon valley of India, Bangalore as well. But with properbig data training in Bangalore professionals can scale net heights and organizations can benefit from their competencies.


Emergers

Business Intelligence Trends and Predictions for 2017

              

2016 brought up some of the most prominent business intelligence software trends. Vendors released a number of products that are affordable yet capable of massive with incredible storage capacity, and ensured those would be available even to smaller companies to boost growth and gain actionable insights. What was particularly striking during this process was the inclusion of new interactive data such as social tweets, videos, and IoT. As some of you will recall, closely 80 percent of this data was not even structured for analysis by that time, and there were no indications it could ever be exported to classic BI systems. The variousbigdata and hadoop training institutes in Bangalore can assist in building the workforce which is needed.
But, here we are. Looking at the list of leading business intelligence companies in the market in 2016, we are actually exploring a world of unlimited possibilities for the future. BI software of today is heavily equipped to undertake all types of analyses, leverage industry data and gauge corporate assets, and is most of all fully enabled to answer the ‘what’s wrong?’ question each time data brainers fail to produce results. What businesses usually like the most about new BI software systems is how they handle assets and capital, rather than plainly controlling leads and extracting practices from their behavior. The rule of today is: all or nothing at all.
Our experts, nevertheless, still lean on the organizational side as the main incentive for BI growth. Systems of today handle unstructured data coming from hundreds of sources, and that’s exactly the state of art we are discussing. Plus, the business intelligence tools you’d purchased in 2016 had definitely been ecosystem-adjusted, mature for flexible deployment, and accessible to non-savvy beginners rather than managers and professionals. And yes – that’s exactly how small companies like it served!
Another thing 2016 taught us to do is to put quality before quantity, which is why we are no longer analyzing whatever comes into our hands. It may be common sense or a product of the Data Provocateur concept forecasted for 2017, but it seems executives are only going to be pickier and more selective. Numerous hadoop training institutes in Bangalore are equipping themselves to nurture and guide the manpower required to take the technology to the next level.
In brief, 2017 is expected to further simplify Big Data analytics for small companies and inexperienced users, and skip the unnecessary learning curves many users struggled with so far. Some of the new systems go as far as to allow full configuration, and let you work with installed BI software whose interactions you’ve already met. Most of all, 2017 is expected to bring self-service and high-performing business intelligence technology.


Emergers

Data management and analysis

              

The battleground for data-enriched CRM will only continue to heat up in 2017. Data is a great way to extend the value proposition of CRM to businesses of all sizes, especially those in the small-to mid-size range. By providing pre-populated data sets, the amount of “busy work” done by sales and other CRM users is reduced, and the better the data, the more effective individuals can be every moment of the day. A lot of M&A as well as in-house development and partnerships will fuel more data-powered CRM announcements in 2017. The key, of course, is seeing which providers provide the most seamless and most sensible use cases out of the box for their customers. The various bigdata and hadoop training institutes in Bangalore can assist in building the workforce which is needed.
In 2017 (and 2018), streaming analytics will become a default enterprise capability, and we’re going to see widespread enterprise adoption and implementation of this technology as the next big step to help companies gain a competitive advantage from their data. The rate of adoption will be a hockey stick model and ultimately take half the time it has taken Hadoop to rise as the default big data platform over the past six years. Streaming analytics will enable the real-time enterprise, serving as a transformational workload over their data platforms that will effectively move enterprises from analyzing data in batch-mode once or twice a day to the order of seconds to gain real-time insights and taking opportunistic actions. Overall, enterprises leveraging the power of real-time streaming analytics will become more sensitive, agile and gain a better understanding of their customers’ needs and habits to provide an overall better experience. In terms of the technology stack to achieve this, there will be an acceleration in the rise and spread of the usage of open source streaming engines, such as Spark Streaming and Flink, in tight integration with the enterprise Hadoop data lake, and that will increase the demand for tools and easier approaches to leverage open source in the enterprise. Numerous hadoop training institutes in Bangalore are equipping themselves to nurture and guide the manpower required to take the technology to the next level.
The unique value creation for businesses comes not just from processing and understanding transactions as they happen and then applying models, but by actually doing it before the consumer, or the sensor, logs in to do something. I predict we will quickly move from post-event and even real-time to preemptive analytics that can drive transactions instead of just modifying or optimizing them. This will have a transformative impact on the ability of a data-centric business to identify new revenue streams, save costs and improve their customer intimacy.
IT will start automating the choices for data management and analysis, leading to standardized data prep, quality, and governance. BI tools have been making more decisions for people and automating more processes. The knowledge for doing this — e.g., choosing one chart type over another — was embedded into the tools themselves. Data prep and management tends to be different, because the required rules are specific to the business requirements rather than being inherent in the data. Rule-based data management will enable IT to define rules that the business uses in its analytics processes, making business analysts more productive while still ensuring reliability and reproducibility. For a use case, consider a data scientist who sources data externally, and lets the data tools automatically choose which enterprise data prep and cleansing processes need to be applied.


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The data hero for 2017

              

IT becomes the data hero. It’s finally IT’s time to break the cycle and evolve from producer to enabler. IT is at the helm of the transformation to self-service analytics at scale. IT is providing the flexibility and agility the business needs to innovate all while balancing governance, data security, and compliance. And by empowering the organization to make data-driven decisions at the speed of business, IT will emerge as the data hero who helps shape the future of the business. The various bigdata and hadoop training institutes in Bangalore can assist in building the workforce which is needed.
In 2017, we’re going to see analytics do more than ever to drive customer satisfaction. As the world of big data exploded, business leaders had a false comfort in having these mammoth data lakes which brought no value on their own when they were sitting unanalyzed. Plain and simple, data tells us about our customers — it’s how we learn more about customers and how to better serve them. As today’s customers expect a personalized experience when interacting with a business, we’re going to see customer analytics become the spinal cord of the customer journey, creating touch points at every level of the funnel and at every moment of interaction.
Knowing the Unknown Unknowns – Enterprises that apply Big Data analytics across their entire organizations, versus those that simply implement point solutions to solve one specific challenge, will benefit greatly by uncovering business or market anomalies or other risks that they never knew existed. For example, an airline using Big Data to improve customer satisfaction might uncover hiccups in its new aircraft maintenance scheduling that could impact equipment availability. Or, a mobile carrier looking to grow its customer base might discover ways to improve call center efficiency. Discovering these unknown unknowns can enable organizations to make changes or fix issues before they become a problem, and empower them to make more strategic business decisions and retain competitive agility. The big data training institutes in Bangalorehave enhanced themselves in offering the best technical expertise available today.
Democratization of Data Analysis – In 2017 we believe that C-suite executives will begin to understand that there is a real gap between their data visions and the ability of their enterprise to move data horizontally throughout the organization. In the past, big data analysis has lagged in implementation compared to other parts of the business being transformed by advanced technology such as supply chains. We believe companies will begin to place different data storage systems into the hands of end users in a fast and efficient manner that has user self-direction and flexibility, democratizing data analysis.


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The Big Data trends

              

If the past 12 months has taught us anything it’s that Big Data is no passing fad. All over the UK and beyond, organizations are embarking on projects deemed critical to the success of the company. If done properly, the collection and analysis of enormous data sets provides the kind of deep insight which can transform customer service and operational efficiency, unlocking competitive advantage.
It’s no coincidence that Gartner predicts the global Big Data market will reach $92.2 billion by 2026 – a CAGR of over 14 percent from 2014. But as organizations finally begin to break down traditional siloes and familiarize themselves with cutting edge technologies from the likes of Splunk, Cloudera, Teradata and SAS, there remain challenges.
These are the five key trends we think are set to shape 2017 as Big Data begins to move from an emerging technology to something truly transformative.
Enter the CDO
“ One of the biggest signifiers that Big Data is going mainstream has got to be the emergence of the Chief Data Officer (CDO). A study from New Vantage Partners this year claimed that over half (54 percent) of Fortune 1000 firms now have such a role, up from just 12 percent in 2012. Although it describes the biggest firms in the US, the effect will be sure to trickle down to other companies as we head into 2017.
The right staff
While at the top end, CDOs will begin to emerge in more organizations, many firms will struggle with skills shortages in general next year. There are simply not enough data scientists and the like entering the workplace to satisfy the huge demand for experts to staff big data projects. Those leaving halfway through a major project can be especially difficult to replace. The various bigdata and hadoop training institutes in Bangalore can assist in building the workforce which is needed.
The new data centre
Alongside, Big Data, “hyper convergence” has been one of the most talked about technology trends of recent years. The idea is to combine storage, compute and network hardware in an appliance to radically improve virtual machine performance and simplify management. The market for hyper converged systems will grow 79% to reach nearly $2 billion in 2016 and we expect even bigger growth next year, with Big Data a major driver.
Big Data to Fast Data
Machine learning and predictive analytics are two of the most hotly talked about tech innovations of recent years – both drawing on Big Data to make predictions about what might happen in the future. As we head into the New Year there’ll be a drive towards speeding up these processes so that users can make real-time decisions. The big data training institutes in Bangalore have enhanced themselves in offering the best technical expertise available today.


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2017 Data Science Prediction: Internet of Things Data Streams to Conquer Traditional Business Intelligence

              

Gartner made these predictions a few years ago, but they will be more relevant in 2017 than ever before. As sensor-driven devices continue to engulf all facets of human society, about 50 percent of Business Intelligence (BI) platforms will capitalize on event data streams. This trend will result in a new breed of BI solutions surfacing on the horizon to capture and harvest real-time data troves from attached devices in a wide range of applications like weather forecasting, manufacturing, electrical, voice recognition, and health monitoring systems, to name a few. Also more and more, as Self-Service Analytics pick up, the analytics capabilities offered by Business Intelligence vendors and those by SaaS providers will become indistinguishable.
According to GE’s Industrial Internet Insights Report, the Internet of Things (IoT) market will contribute between $10 and $15 trillion to global GDP in the next 20 years, which can be witnessed in the rising popularity of IoT skills in the Data Science marketplace. IBM, Intel, Verizon, and Microsoft are all aggressively hiring Data Scientist manpower with IoT skills. The various bigdata and hadoop training institutes in Bangalore can assist in building the workforce which is needed.
Big Data Technology Spending will Boom
“ Gartner also predicted that the confusion and uncertainty surrounding the business impact of Big Data was foreseeable until 2016. True to that prediction, much of the debate around the real vs. perceived value of Big Data has been already resolved, and Big Data technologies have matured from their earlier “emerging” stage. Today, Big Data technologies are more mainstream and more necessary for the success of Data Science initiatives than they have been at any time in the past. 2017 will only increase this important relationship. The big data training institutes in Bangalore have enhanced themselves in offering the best technical expertise available today.
With the growing promise of Big Data solutions, 2017 will see a natural growth of technologies like Hadoop as it has already proven to have a positive impact on enterprise IT budgets. Hadoop will not only continue to deliver a centralized platform for cleansing, storing, and processing huge volumes of data, but it will also combat the cost-prohibitive nature of standard IT solutions. Hadoop offers an excellent solution to deal with a wide variety of applications like Predictive Analytics, ETL, Data Visualization, Data Mining, Data Warehousing, IoT, or Click stream Analysis. Today, Hadoop is considered one of the most preferred single, scalable, and cost-friendly alternatives to commercial Big Data Management systems; its popularity will increase through 2017.
The only constraint that hindered the growth of Hadoop in 2015-16 was revenue generation, but finally the rising popularity of Big Data technologies will open a revenue market for Hadoop. The Hadoop Market Forecast 2017-2022 forecasts that this expanding market will surpass $16 billion by 2020. Also, read about this Hadoop and Big Data Analytics Market report, which indicates that the close inter-dependency of both the markets will result in a worth around $13.9 billion by the end 2017.


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The Power of Data Science

              

A particular McKinsey report published recently predicted that the global business community would feel the pinch of an acute shortage of Data Science professionals for the next decade, specifically a shortage of “1.5 million analysts” skilled at deriving competitive intelligence from the vast amounts of static and dynamic (real-time) data. While such a prediction is coming true, a greater focus on marketing the importance of Data Management to enterprises and within higher education institutions is enabling the entire industry to cope with shortages in ways that were not fully understood only a few years ago. The upheavals within the Data Science industry will continue throughout 2017, but so will more growth and more possibility. The various big data and hadoop training institutes in Bangalore can assist in building the workforce which is needed.
To understand why Data Science is so critical for business success, there are a few pre-conditions that need to be understood: Data Science has the requisite capability to provide accurate solutions to business problems when one needs it and where one needs it.
“Data Science enables better business decisions and accurate study of the impact of such decisions. A past Harvard Business Review study stated that top businesses are generally 6 percent more profitable than their peers when they rely on data-enabled decisions.
Data Science can make more exact predictions about the future when both human intuition and experience fail. With Data Science, businesses do not have to depend on guesswork anymore.
Customer tracking has become a reality with highly capable, smart devices and state-of-the analytics platforms. Real-time customer data acquisition helps deliver accurate answers
Given the above information, it is possible to understand why Data Science is going through a global revolution at this juncture in time. The limitations of science and technology that had hitherto withheld the power of Data Science are gradually eroding, and the Data Management industry can expect some major changes to sweep through global Data Science practices in 2017. Some calculated predictions about where the Data Science industry is headed next year are listed below. The big data training institutes in Bangalore have enhanced themselves in offering the best technical expertise available today.
Machine Learning to Rule the Industry
Quora featured a query about how Machine Learning will impact the evolution of the Data Science industry. To answer this query, Claudia Perlich, Chief Scientist at Distillery and Adjunct Professor at NYU, confirms that given the close relationship of Data Science and Machine Learning (ML), the future business analytics world will not be able to survive without ML. Perlich expects that as ML is increasingly becoming more relevant to Data Scientists, a basic skill level in Machine Learning will soon become mandatory to even begin a career in Data Science. Read the full explanation in Forbes blog post titled Machine Learning Will Bring Some Big Changes to Data Science as We Know It.
The Machine Learning fever will continue to envelop Data Scientists in 2017. Organizations will go the extra mile to locate and attract Data Scientists will solid Machine Learning skills to enrich their Data Science Departments.


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Growing Big data

              

Market research and advisory firm Ovum estimates the big data market will grow from $1.7 billion in 2016 to $9.4 billion by 2020. As the market grows, enterprise challenges are shifting, skills requirements are changing, and the vendor landscape is morphing. The coming year promises to be a busy one for big data pros. One of the key predictions from industry watchers and technology players is that there will be an increase in the demand data scientist.
TDemand for data scientists is softening, suggests Ovum in its report on big data trends. The research firm cites data from Indeed.com that shows flat demand for data scientists over the past four years. At the same time, colleges and universities are turning out a greater number of graduates with data science credentials. The various bigdata and hadoop training institutes in Bangalore can assist in building the workforce which is needed.

“Who is recruiting these prospects? In all likelihood, excluding online digital businesses, relatively few enterprises outside the Global 2000 are absorbing them, and few would have any idea of how to use data scientists,” Ovum writes

Data is now creating opportunities for business growth and profit like never before. In the last decade, the emergence of advanced data technologies and superior analytics tools has made it possible for business operators to reap numerous benefits from their data assets, yet for most they’ve only just scratched the surface of data’s potential. Data Science is allowing enterprise’s to successfully leverage that potential like never before.

The spread of self-service data analytics, along with widespread adoption of the cloud and Hadoop, are creating industry-wide change that businesses will either take advantage of or ignore at their peril. The reality is that the tools are still emerging, and the promise of the (Hadoop) platform is not at the level it needs to be for business to rely on it. Numerous hadoop training institutes in Bangaloreare equipping themselves to nurture and guide the manpower required to take the technology to the next level.


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Big Data Avenues For Further Development

              

Due to the increasing diffusion of electronic devices and data-led services, the total amount of information stored by humanity doubles every two years. Big data, “chunks of data too big to be processed through common software packages”, is getting bigger and ubiquitous. However, the offer of big data software and solutions has also reached maturity, and a number of opportunities arise for businesses who want to take advantage of this technology. The various bigdata and hadoop training institutes in Bangalore can assist in building the workforce which is needed.
This blog summarizes the state-of-the-art of big data solutions and suggests avenues for further development of the technology.
From Data to Metadata
Nowadays, the focus of big data technology is no more on the narrow informative content, but on the broader context in which the data has been collected. This means that data will cover only a minor role in the immediate future and metadata, which describes the data and provides additional value, will increasingly become important and complex. A big data application can be imagined similar to a shopping cart. One can easily see the data (i.e. the content of the cart) at any point in time. The big data training institutes in Bangalore have enhanced themselves in offering the best technical expertise available today.
However, little value emerges from looking at a single purchase. Basic information such as price, weight, size and content of the item is immediately available, but interesting pieces of information are harder to collect. In the shopping cart of big data, the item purchased is not at the centre of attention. Instead, additional information (i.e. metadata) enables one to answer several questions: who purchased the item? When? Where?
Thus, one can imagine big data as a smart shopping cart capable of keeping track of and elaborating extra information about the purchases.
Aggregation and Meaning
Nevertheless, metadata alone is not enough to build competitive big data applications. Metadata constitutes the first layer of operation and serves as a basis for aggregating multiple items in a relevant way.
Sets of data related by comparable meta-data can be grouped and analyzed together to obtain significant insights on customer behavior and sales forecasts. In a grocery store, purchases could be grouped under several metrics. For example, time series of a single item’s sales can be used to predict future sales of that item, or an analysis of past consumer purchases can yearn inferences on his or her preferences.


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Focus on big data, IoT for new growth

              

Karnataka will focus on creative, disruptive and emerging technologies in the Internet of Things (IoT), artificial intelligence, robotics, aerospace, cyber security, big data analytics and machine learning, Karnataka IT Minister Priyank Kharge said on Saturday.
“Innovative disruption fuels growth. The state has already framed a startup policy, set up startup warehouses and created venture funds for the biotechnology sector. It is also acting as an angel investor to fund ideas through idea2POC initiative, “he said. He referred to the flagship IT event of the state, BengaluruITE.biz, and how the theme of the latest edition, Define the Next, was chosen.
The minister pointed out that new-age startups have a direct impact on cities they make their homes, alluding to how Infosys changed Bengaluru in the mid-90s, Chinese e-commerce giant Alibaba impacted Hangzhou or Google changed the face of Mountain View.
Karnataka houses more than 4,900 startups as per the Global Startups ecosystem ranking report of 2015, he said.


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ETL Testing/Bigdata & Hadoop Testing/Bigdata

              

ETL Testing/Bigdata & Hadoop Testing/Bigdata
Classroom/Online Training
SWE With 2+ yrs of Exp in Manual/Selenium/Web Application Testing
Of Bank /Retail And Insurance
Upgrade Your Knowledge For Better Opportunities.
"In Bigdata - Scripting Inside OZZE " - Focused


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Big Data Trends For The Future

              

In a new survey conducted by Syncsort, 250 prominent respondents including data architects, IT managers, developers, business intelligence/data analysts, and data scientists weigh in on big data trends to watch in the future. Two-thirds of those surveyed work in companies with over $100 million in annual revenue. Industries represented are financial services, healthcare, government, and retail. The big trend is the move away from Hadoop experimentation into full production with big data analytics.
The future big three trends are:
Apache Spark production deployments Conversion from other platforms to Hadoop Leveraging Hadoop for advanced use cases The uptick in Apache Spark is a bit of a surprise at a full 70 percent of respondents stating that Spark is the platform that they're most interested in. MapReduce came in at a distant second at 55 percent. However, Syncsort's big data analysts predict that MapReduce will remain the primary compute framework for production deployments. But the numbers tell a different story. With 70 percent of the respondents expressing a keen interest in Apache Spark, MapReduce deployments may in fact reduce over the next twelve months.
TPeople are often hung up on the volume aspect of big data but other factors can be just as telling in the issues they raise for business. The two primary factors in this interest in Spark is that it is easy to deploy and its speed. Because Spark runs in memory, it requires big iron. Its speed also highlights one of MapReduce's biggest problems: its high-latency, batch-mode response.
But like the Syncsort experts, I believe that people will hang onto MapReduce for a while longer. The conversion or offload from expensive platforms to open source Hadoop is a significant shift. The old mainstays of mainframe and the enterprise data warehouse are becoming too expensive to deal with when cheaper alternatives are screaming for attention. The respondents agree to the tune of 63 percent stating that Hadoop will help them increase business and IT agility. Fifty-five percent expect to increase operational efficiency and reduce costs. And 51 percent want to use Hadoop to make more data available to business users. Numerous hadoop training institutes in Bangalore are equipping themselves to nurture and guide the manpower required to take the technology to the next level.
More than half the respondents view Hadoop as a way to innovate by using social media data and data from IoT sources. Oddly, only 4.9 percent reported interest in advanced use cases involving mobile apps and software. The various bigdata and hadoop training institutes in Bangalore can assist in building the workforce which is needed.


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Big data for 2017

              

Last year the big data market centered squarely on technology around the Hadoop ecosystem. Since then, it’s been all about ‘putting big data to work’ to generate ROI from increased revenue and productivity and lower risk. Now, big data continues its march beyond the crater. In 2017 we can expect to see more mainstream companies adopting big data and IoT, with traditionally conservative and skeptic organizations starting to take the plunge. There will also be a dearth of professionals who can handle the change and bigdata and hadoop training in Bangalore is available to make a difference.
Data blending will be more important compared to a few years ago when we were just getting started with Hadoop. The combination of social data, mobile apps, CRM records and purchase histories via advanced analytics platforms allow marketers a glimpse into the future by bringing hidden patterns and valuable insights on current and future buying behaviors into light.
The spread of self-service data analytics, along with widespread adoption of the cloud and Hadoop, are creating industry-wide change that businesses will either take advantage of or ignore at their peril. The reality is that the tools are still emerging, and the promise of the (Hadoop) platform is not at the level it needs to be for business to rely on it.
As we move forward, few trends shaping the world of big -Data:
The Internet of Things (IoT): Businesses are increasingly looking to derive value from all data; large industrial companies that make, move, sell and support physical things are plugging sensors attached to their ‘things’ into the Internet. Organizations will have to adapt technologies to map with IoT data.
Deep Learning: , Deep learning, a set of machine-learning techniques based on neural networking, is still evolving, but shows great potential for solving business problems. It enables computers to recognize items of interest in large quantities of unstructured and binary data, and to deduce relationships without needing specific models or programming instructions.
In-Memory Analytics: Unlike conventional business intelligence (BI) software that runs queries against data stored on server hard drives, in-memory technology queries information loaded into RAM, which can significantly accelerate analytical performance by reducing or even eliminating disk I/O bottlenecks. With big data, it is the availability of terabyte systems and massive parallel processing that makes in-memory more interesting.
It’s all on Cloud: Hybrid and public cloud services continue to rise in popularity, with investors claiming their stakes. The key to big data success is in running the (Hadoop) platform on an elastic infrastructure. We will see the convergence of data storage and analytics, resulting in new smarter storage systems that will be optimized for storing, managing and sorting massive petabytes of data sets. Going forward, we can expect to see the cloud-based big data ecosystem continue its momentum in the overall market at more than just the “early adopter” margin.
Companies want a platform that allows them to scale, something that cannot be delivered through a heavy investment on a data center that is frozen in time. For example, the Human Genome Project started as a gigabyte-scale project but quickly got into terabyte and petabyte scale. Some of the leading enterprises have already begun to split workloads in a bi-modal fashion and run some data workloads in the cloud. Many expect this to accelerate strongly as these solutions move further along the adoption cycle.


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Need for ETL

              

ETL comes from Data Warehousing and stands for Extract-Transform-Load. ETL covers a process of how the data are loaded from the source system to the data warehouse. Currently, the ETL encompasses a cleaning step as a separate step. The sequence is then Extract-Clean-Transform-Load. Let us briefly describe each step of the ETL process. Extract .The Extract step covers the data extraction from the source system and makes it accessible for further processing. The main objective of the extract step is to retrieve all the required data from the source system with as little resources as possible. The extract step should be designed in a way that it does not negatively affect the source system in terms or performance, response time or any kind of locking.
Update notification - if the source system is able to provide a notification that a record has been changed and describe the change, this is the easiest way to get the data.
Incremental extract - some systems may not be able to provide notification that an update has occurred, but they are able to identify which records have been modified and provide an extract of such records. During further ETL steps, the system needs to identify changes and propagate it down. Note, that by using daily extract, we may not be able to handle deleted records properly.
Full extract - some systems are not able to identify which data has been changed at all, so a full extract is the only way one can get the data out of the system. The full extract requires keeping a copy of the last extract in the same format in order to be able to identify changes. Full extract handles deletions as well.
ETL tools like informatica, datastage, abinitio etc are becoming popular in building a data warehouse. ETL tools are used because of the following reasons:
ETL tools can connect and read data from multiple sources like relational databases, flat files, xml files, cobol files etc. The capability of connecting and reading data from different sources is readily built in ETL tools. As an user you don’t need to write a code for this. If you have used a programming languages, you have to write your own code for connecting to multiple sources and reading. Hence, one can say that the need of the hour is ETL testing institutes in Bangalore, which can offer all the above mentioned programmes in a pocket friendly manner.


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Why Hadoop is Needed

              

Hadoop is changing the perception of handling Big Data especially the unstructured data. Let’s know how Apache Hadoop software library, which is a framework, plays a vital role in handling Big Data. Apache Hadoop enables surplus data to be streamlined for any distributed processing system across clusters of computers using simple programming models. It truly is made to scale up from single servers to a large number of machines, each and every offering local computation, and storage space. Instead of depending on hardware to provide high-availability, the library itself is built to detect and handle breakdowns at the application layer, so providing an extremely available service along with a cluster of computers, as both versions might be vulnerable to failures. One can say that there is a need of hadoop professionals which can be fulfilled by hadoop training in Bangalore. .Hadoop Distributed FileSystem (HDFS)
HDFS is designed to run on commodity hardware. It stores large files typically in the range of gigabytes to terabytes across different machines. HDFS provides data awareness between task tracker and job tracker. The job tracker schedules map or reduce jobs to task trackers with awareness in the data location. This simplifies the process of data management. The two main parts of Hadoop are data processing framework and HDFS. HDFS is a rack aware file system to handle data effectively. HDFS implements a single-writer, multiple-reader model and supports operations to read, write, and delete files, and operations to create and delete directories.
Tremendous opportunities are there with big data as the challenges. Enterprises that are mastered in handling big data are reaping the huge chunk of profits in comparison to their competitors. The research shows that the companies, who has been taking initiatives through data directed decision making fourfold boost in their productivity; the proper use of big data goes beyond the traditional thinking like gathering and analyzing; it requires a long perspective how to make the crucial decision based on Big Data.
With the enterprise data warehouse approach, organizations find their data scattered across many systems and silos. This decentralized environment can result in slow processing and inefficient data analysis. Hadoop makes it possible to consolidate your data and business intelligence capabilities within an Enterprise Data Hub.


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How Big Data is Changing Business

              

Big data differs from constricted applications that look at just one source of data, yielding small answers. Big data examines a broad range of sources that include structured information such as purchase customer relationship management (CRM), histories, data and intelligence from industry partners, as well as unstructured information such as social media. Big data analytics also brings unstructured data into the fold, information gleaned from blogs, videos, social media feeds and other sources. Sorting through this information needs professionals who are proficient in their work, and have taken big data courses in Bangalore. Expanding customer intelligence is just one trend—as the technology evolves, using big data will accelerate numerous trends over the coming year like improving operational efficiencies. Big data has finally forged the last links of the value chain that can help companies drive more operational efficiencies from existing investments. What is needed are well learnt individuals, which can be achieved by opting for big data training in Bangalore from some ace institutes like Emergers Technologies.
Such institutes educate the young and bright on how the feedback loop is created by data generated in the field, and it’s growing at a pace that’s hard to comprehend. How sensors on a single commercial aircraft generate 20 terabytes of data an hour and automobiles are reporting back data collected from onboard sensors and dealer service systems. These incredible repositories of data, combined with machine-to-machine interaction, are fueling a new wave of predictive analytics, services that enable equipment to determine their own maintenance schedule, and all these things can be learnt through best embedded training institute in Bangalore.
One can say big data is moving from the realm of data scientists into everyday business transactions and encounters. In call centers, analytics-infused CRM systems can review multiple data sources in real time to suggest offers that a representative can present to a customer. At the doctor’s office, analytics integrated into a health maintenance app may improve outcomes by presenting the physician with informed suggestions and next steps to consider in treating a patient.
As companies become more data-driven, it’s only natural that those insights find their way into the hands of people who can put them into action like professionals who have taken proper training from big data training in Bangalore. As mobility accentuates the impact of big data on both customer intelligence and operational efficiency by making everything immediately actionable—armed with immediate decision-making capability and intelligence are going to be well trained professionals and personnel’s who will be making a difference in the various big data organizations.


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Why Embedded Systems are Important

              

Embedded systems are small, fast, and very powerful tools, gadgets and equipments which have become part of our everyday life. They are those computer systems that do not look like computer systems to the everyday user. They form a part of a larger system or product, part of anything, from mobile phones to medical devices, from agricultural farming tools to manufacturing equipments. An embedded system is a micro-processor based system that is built to control a function or range of functions and is not designed to be used by the user in the same way that a personal computer (PC) is (Heath, 2003).
It is a combination of computer hardware and software, and perhaps additional mechanical or other parts, designed to perform a dedicated function. In some cases, embedded systems are part of a larger system or product, as in the case of an antilock braking system in a car. Although the user can make choices concerning the functionality, he cannot change the functionality of the system by adding or replacing software as is possible with the PC. There is a need for professionals to take embedded course in Bangalore in order to polish their skill sets.
Why do we need embedded systems?The first reason why we need embedded systems is because general-purpose computers, like PCs, would be far too costly for the majority of products that incorporate some form of embedded system technology (Christoffer, 2006). Another reason why we need embedded systems is because general-purpose solution might also fail to meet a number of functional or performance requirements such as constraints in power-consumption, size-limitations, reliability or real-time performance etc.The digital revolution, started decades ago, has reached a stage that we cannot conduct our normal modern daily lives without this technology. Indeed, it is safe to say that we already own at least one piece of equipment, which contains a processor, whether it is a phone, an automatic washing machine, a television or an MP3 player.
On the embedded software side, the implementation is designed to put the least possible computation load on the main processing unit, reducing the power consumption as a result. The implementation is paralleled among different input/output (I/O) and computation modules to achieve real-time responses for gesture recognition algorithms. We also make use of techniques such as direct-memory-access (DMA), which reduces the load on the CPU by directly handling the I/O module’s access to main memory, thereby reducing power consumption.


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Demand for Big Data and Hadoop Professionals

              

Organizations generate 2.5 Quintilian bytes of data. So much is the impact that 90 percent of the data in the world today has been set up in the last two years alone. Collecting and examining Big Data gives organizations enhanced insight, assessment capability, and process automation. Formatting unstructured data makes it suitable for data mining and analysis, here Hadoop has culminated into a core platform for structuring Big Data. It also resolves the problem of formatting it for analytic rationale. Hadoop uses a distributed computing architecture consisting of many servers using commodity hardware.
According to industry experts in next three years more than half of the data in this world will move to Hadoop? No wonder McKinsey Global Institute estimates shortage of 1.7 million Big Data professionals over next three years. With growing IT sector, Bangalore is also facing the dearth in qualified professionals.
Considering this increasing gap in the demand and supply, with the help of Big Data and Hadoop training in Bangalore, IT/ ITES professionals can get rewarding opportunities and boost their career by gaining the most sought after Big Data Analytics skills. There are numerous institutes offering Big Data and Hadoop training in Bangalore where the training attendees will gain practical skill set on Hadoop in detail, including its core and latest components, like MapReduce, HDFS, Pig, Hive, Jasper, Impala HBase, Sqoop, Flume, Oozie, Zoopkeeper, Spark and Storm. For extensive hands-on practice, in both Hadoop online training and classroom training aspirants will get admittance to the virtual lab and numerous assignments and projects for Big Data certification. At end of the program from one of the Big Data training institutes in Bangalore candidates are awarded Big Data Certification on successful completion of projects that are provided as part of the training.

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