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How Big Data Analytics Power Profits for the Hospitality Industry

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How Big Data Analytics Power Profits for the Hospitality Industry

The hospitality industry is highly dependent on customer satisfaction. And the analysis of big data can help this industry predict customer behavior by understanding their needs and expectations. This in turn enables the hotels and restaurants to provide personalized customer service and retain loyal customers.

Hospitality service provider Airbnb is making the most of the new ‘’mobile first’’ approach where responsive designs are created for the smallest screens. This mode allows customers to engage in Airbnb business through phones. Although big data and its analysis is a large part of the success for this industry, many companies are yet to fully understand the gains associated with big data.

Here are some ways how big data enables the hospitality industry to drive profits:

Take better control of business:

Effectively analyzing big data drastically changes how the business runs. The hotel industry is a data rich sector with massive volumes of web, audio and video content. However, many hotels don’t use their data to its full potential. For instance, hoteliers collect loyalty information but few exploit the data for making business decisions. Through analytical data exploitation, hotels can deepen their understanding of the behavior, needs and expectations of guests and develop better loyalty programs.

Customer segmentation and Targeting:

Hotels must use customer data to provide better customer service as that is essential for ensuring that customers return to avail their services again. Analyzing this data is crucial to segment customers based on booking and travel trends, preferences, chance of responding to promotions, etc. Targeting clients with wrong offers can hinder business growth. Data analysis allows them to retain their best repeat clients by good incentives and promotions. It also allows them to build separate deals for customers who don’t visit them often with the hopes of converting them to loyal customers.

Set best prices for rooms:

Big data analytics is very important for setting competitive hotel prices so that it attracts more guests. Apart from setting the best price for rooms, hospitality-driven businesses can optimize the budget for utilities through analysis of weather data and energy rates.

On-time delivery:

As big data tools become more and more advanced, it shall enable better collection of data from traffic, temperature, weather, route and other sources. This will improve food delivery by providing better estimates of time taken to deliver. Moreover, it shall help restaurants understand how all the aforementioned sources affect the quality of food. Thus, it helps to plan the transportation beforehand and optimizes the utilization of resources.

Menu enhancement:

Using the customer data on food preferences, restaurants can build a customer profile that contains their favorite food and drinks. From the data gathered through feedback forms and online surveys, they can identify the most popular items in their menu and determine whether their menu needs to be improvised or completely reengineered.

Hence, new sources of data and emerging technologies like IoT (Internet of Things) and AI (Artificial Intelligence) enable the hospitality industry to understand the current trends in the market and boost the overall profit of the enterprise.

Companies who are embracing the power of big data are reaping huge profits, and students who are enrolling for big data Hadoop courses are earning big bucks! So, unlock your career with a big data Hadoop certification in Gurgaon. And follow DexLab Analytics for the latest big data related blogs and information.

References:

www.smartdatacollective.com/hospitality-industry-emergence-big-data

www.hiddenbrains.com/blog/big-data-analytics-driving-restaurant-industry-towards-profitable-growth.html

insidebigdata.com/2018/08/03/three-industries-profiting-big-data

 

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Tapping Into Big Data for Better Talent Acquisition

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Tapping Into Big Data for Better Talent Acquisition

There are many variables that need to be considered while making hiring decisions. Most importantly, there’s need to fill skill gap. Other factors are candidate behavior and financial aspects of hiring, like cost for training new employees. Big data and analytics help form valuable insights into the job market. Consider the example of IBM acquiring the services of consulting firm Kenexa. It was used to access data of 40 million workers in order to find the personality trait most suitable for a sales job. All kinds of information starting from the workers’ job applications to managerial level was analyzed and it was determined that ’persistence’ is the most valued trait.

Here are some important ways big data helps firms attract promising candidates:

Automate HR Affairs

Talent Acquisition encompasses a wide variety of tasks and when HR teams work in tandem with AI then many day-to-day tasks gets simplified. It helps with tasks like filtering and tracking application status of candidates, getting new hires onboard and making future decisions about employees by analyzing data of previous employees. Data enabled systems saves a lot of time and makes tedious tasks much easier.

Predictive Analytics for Better Hiring Decisions

Hiring professionals need 360 degree information about a particular situation in order to make the best decision possible. They need to analyze everything starting from the human capital requirement in the organization to the economics. Big data enables them to form a clear idea about the skill gaps in the company’s workforce, analyze current trends in the market, follow the financial KPI’s and demographic traits associated with hiring, set the hiring quota and identify the skills and talents to look for in new hires.

Discard ‘’Eleventh Hour’’ Hiring Method

The urgency to fill skill gaps often pressurizes HR professionals to make quick hires, which can be impulsive and not the best. With the help of predictive analytics, these last minute situations can be completely avoided. It allows HR teams to form long-term hiring strategies that align with company goals and also enables them to make timely hires. Using the power of big data, you can be aware of the future needs of your company and job market trends. Hence, it helps eliminate panic situations where you make a hire only to realize later that he/she doesn’t fit the bill.

Social Media for Insights

Big data helps firms attract the right candidates that fit a role. The hard data available on the social media platforms of promising candidates and their search behavior online give organizations crucial information that help them make right decisions. Talent Bin is one of the many employment websites that use information from social media to form insights.

Targeted Job Ads

With the help of analytics, companies can create target groups and rope them in by showing relevant ads. For example, if there’s a financial service provider who enjoys a large talent network interested in marketing on LinkedIn, then they can take this opportunity to post marketing-specific job advertisements. Many potential candidates might find these posts engaging and the company will find the right fit for the job.

Wrapping up, we can say that big data has opened up fresh avenues to make better hires. The influence of big data in every aspect of the modern corporate sector is truly astounding. The smartest candidates are enrolling for big data courses to build skills that sell the most in today’s world of work. For expert-guided big data Hadoop training in Gurgaon, visit DexLab Analytics.

 

Reference: insidebigdata.com/2018/07/20/big-data-talent-acquisition-effective-synergy-make-better-hires

 

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3 Recent Applications of AI will leave you Spellbound

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3 Recent Applications of AI will leave you Spellbound

AI technology has the potential to enhance societies in a number of ways. Here, we discuss some of latest developments in AI-based research.

AI can smell illness in your breath

According to a recent declaration made by Nvidia, AI can detect illness, including cancer, by analyzing the human breath. Researchers from Edinburgh Cancer Center in UK, Loughborough University, the University of Edinburgh and Western General Hospital have developed an AI program using deep learning methods that is  able to analyze compounds in human breath and predict illness. The motivation? Humans have a less developed sense of smell compared to other animals. Hence, a lot of information hidden in the air around us go unnoticed and can be perceived with a highly receptive olfactory system.

Source: news.developer.nvidia.com

The team of researchers said that this is the first machine learning model that can successfully detect compounds and ion patterns from raw GC-MS (Gas Chromatography and Mass Spectrometry) data. TensorFlow deep learning frameworks, cuDNN-accelerated Keras and Nvidia Tesla GPUs were used to develop neural networks for the program. The data utilized for expanding the neural networks was contributed by volunteers who had different forms of cancer and were undergoing radiotherapy. Artificial intelligence makes the process less expensive, and definitely more reliable and faster than humans analyzing a breath sample.

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AI is marking exam papers

A new concept is coming together in China’s education system. Experiments suggest that machine intelligence can contest a teacher’s marking capability and at times even surpass it! AI has long assisted humans in marking multiple choice exams and performed wonderfully in that. Chinese researchers have taken the examining powers of AI-driven machines a step forward and developed AI that can mark essays.

First, the system perceives general logic from the context and then links it to the meaning of words. It works like a human mind that first understands the theme of the story from the headline and then reads through the rest of the writing. The machine learning algorithm assesses the quality of the essay with human-like judgment. It grades the paper and provides remarks on areas where there’s scope of improvement. These remarks include the need to improve sentence structure and writing approach among others.

Source: Cambridge assessment

A case study conducted with 120 million students from 60,000 schools shows that both the algorithm and human teachers have the same average performance rating, which is 92%. However, the model is designed to automatically improve as it handles more tasks and is likely to outperform the teachers in future.

Secret Archives of Vatican being decoded with AI

Within the walls of the Vatican lies the most impressive collection of historical facts in the world. The Vatican Secret Archives contains records that date back to more than 12 centuries. Despite gazillions of pages stored in Vatican, only a selected few are available to researchers and scholars online.

Source: Serial Box

A new project named In Condice Ratio is combining optical-character-recognition (OCR) with artificial intelligence to help scan through all the information and upload it to online database. Traditional OCR method isn’t effective on handwritten documents. But the new OCR enhanced with AI, known as jigsaw segmentation, can recognize different pen strokes and turn the raw information into searchable data.

Source: In Condice Ratio

What the future holds

It seems like in the near future humans beings will need to use and depend on the judgment of AI applications on the daily. So, why not master the necessary skills needed to understand the workings of AI applications? Enroll for machine learning courses in Gurgaon and follow DexLab Analytics for the latest AI-tech blogs. We provide top-notch machine learning training in Delhi.

 

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#JobTrends: Open Data Analytics Jobs in India Is Set To Double in 2018

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#JobTrends: Open Data Analytics Jobs in India Is Set To Double in 2018

Prediction says – the demand for AI and Big Data Analytics jobs is expected to hit 5.11 lakh, but professionals possessing the desired skills will number only 3.7 lakh by the end of 2018 – according to the National Association of Software and Services Companies (Nasscom). 

Further, the demand is expected to spike up to 7.86 lakh by the end of 2021.

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No wonder, the Indian IT industry is exploding with lucrative opportunities – 2018 began witnessing a steep rise in demand for skilled consultants specialized in the quarters of emerging technologies, like machine learning and artificial intelligence as well as big data and analytics. And, with a steady focus on Digital India, the IT recruitment industry is on its wheels to add 50% more workforce, resulting in another 1.80 to 2.0 lakh job creation by the end of this year.

Artificial Intelligence alone has the ability to generate 2.3 million jobs globally by 2020, says Alka Dhingra, GM, IT Staffing, TeamLease Services, a leading recruitment company. 

Revival of Indian IT sector

Since the technology is taking charge and rapidly transforming the every facet of business, the World Economic Forum has predicted a net loss of 5 million jobs in a couple of years. However, this leaves little room for worry, because job seekers and skilled professionals possessing the desired skills will be in a comfortable position to capitalize this trend and strive for better.

In this context, “Priority focus for us would be re-skilling the workforce in AI and big data,” says Debjani Ghosh, President, Nasscom, further adding, “Of the 4 million jobs in the industry, the nature of 60-65% is likely to change over the next five years.”

Quite interestingly, 1 out of 5 companies are found using AI to boost decision-making capacity. It help companies provide curated customized solutions and instructions to techies in real-time. Back in the day, traditional text analytics platforms were extremely complex; a handful number of companies were lucky enough to successfully analyze text data. But now, with Deep learning in AI, analysis of structured and unstructured text data has become a piece of cake – as a result of which, “We expect a 60 per cent increase in demand for AI and machine learning specialists in 2018,” shares BN Thammaiah, Managing Director, Kelly Services India.

Just like their job responsibility, the pay package of an AI professional breathes of adequacy – a techie with 2-4 years of experience earns 15-20 lakh INR annually, whereas 4-8 years of experience leads to 20-50 lakh INR annually.  

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New Streams to Consider

Retail, healthcare, telecom and manufacturing – these sectors are going to first witness the big data impact, followed by automobiles and FinTech. The next 5 years is going to be pivotal. Companies would be struggling hard to find and appoint AI engineers, especially for positions relating BI and Cloud for industrial automation. BlockChain is another new-age digital discipline that has started shifting focus and drawing attention across the e-com industry. It is found penetrating the sector, and for good reasons.

Now, if you are a data-enthusiast and seeking ways to reap benefits out of such a magnanimous tech-revolution? We got your back. DexLab Analytics offers state of the art Big Data training in Gurgaon at the best prices. Learn more.

 

The blog has been sourced from —

www.thehindu.com/business/Industry/ai-big-data-will-require-51-lakh-people-in-2018/article24534536.ece?utm_campaign=socialflow

www.thehindubusinessline.com/info-tech/big-data-machine-learning-ai-to-shape-job-market-in-2018/article10006991.ece

 

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Big Data Analytics: 10 Data-Slurping Things Everyone Should Know

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Big Data Analytics: 10 Data-Slurping Things Everyone Should Know

Big Data is no more a fleeting obsession. With numbers. It’s the beginning of a cognitive revolution that’s touching every facet of life and business on this planet.

Thanks to technological advancement, we’re churning more data than ever before. In fact, a lot more. And for good reason.

Every second we create new data – Don’t believe me?

Here are 10 mindboggling stats about big data – how it’s created, ways it’s being used and how much of it is still out there waiting to AMAZEEE us!!!

In short, this convinces us why we can’t afford to ignore big data and analytics:

Data volumes are exploding – the way it’s growing, by the end of 2020, it would generate 1.7 megabytes of new data every second for every human being living on this planet.

In a couple of years, our aggregated digital reservoir of data will expand from 4.4 zettabytes to approximately 44 zettabytes, or 44 trillion gigabytes.

Facebook users view 2.77 million videos and send 31.25 million messages, on an average every minute.

Whaaaat??!!!

Too much to process??

Wait, till you hear this!

Every minute up to 300 hours of video are being uploaded on YouTube, alone.

 Yes, while you are reading this blog, loads of users are already uploading chunks of content online.

For that reason or other, within the next 5 years, there will be more than 50 billion smart connected devices in the world, all powered by cutting edge data analysis technology.

Be ready to collect, analyze and share data without batting eyelids.

By 2020, one third of total data will roll over to the cloud (a concentrated network of servers all connected through the Internet)

Distributed Computing is the future. Google uses it involving 1000 computers to solve a single search query within 0.2 seconds. Woah!!!

Hadoop market is expected to grow at a compound annual growth rate 58% beating $1 billion mark by 2020.

The White House is heard to have invested more than $200 million in big data projects.

Now, the most spectacular fact is that less than 0.5% of all data is analyzed and used till now… So, just imagine the potential it withholds!!

In the next five years, big data is going to touch the moon, and what about you?! Don’t you feel like joining the data-inspired bandwagon?

Go, grab a quick Big Data Hadoop training in Gurgaon — and fill in oodles of knowledge, skill and expertise for improving your career graph and business performance. For more information on big data hadoop certification, drop by our expert website of DexLab Analytics.

The blog has been sourced from —

https://www.forbes.com/sites/bernardmarr/2015/09/30/big-data-20-mind-boggling-facts-everyone-must-read/#6a5cef7817b1

https://www.datasciencecentral.com/profiles/blogs/15-astonishing-tweetable-facts-about-analytics

 

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The 8 Leading Big Data Analytics Influencers for 2018

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The 8 Leading Big Data Analytics Influencers for 2018

Big data is one of the most talked about technology topics of the last few years. As big data and analytics keep evolving, it is important for people associated with it to keep themselves updated about the latest developments in this field. However, many find it difficult to be up to date with the latest news and publications.

If you are a big data enthusiast looking for ways to get your hands on the latest data news, then this blog is the ideal read for you. In this article, we list the top 8 big data influencers of 2018. Following these people and their blogs and websites shall keep you informed about all the trending things in big data.

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Kirk Borne

Known as the kirk in the field of analytics, his popularity has been growing over the last couple of years.  From 2016 to 2017, the number of people following him grew by 30 thousand. Currently he’s the principal data scientist at Booz Allen; previously he has worked with NASA for a decade. Kirk was also appointed by the US president to share his knowledge on Data Mining and how to protect oneself from cyber attacks. He has participated in several Ted talks. So, interested candidates should listen to those talks and follow him on Twitter.

Ronald Van Loon

He is an expert on not only big data, but also Business Intelligence and the Internet of Things, and writes articles on these topics so that readers become familiar with these technologies. Ronald writes for important organizations like Dataconomy and DataFloq. He has over hundred thousand followers on Twitter. Currently, he works as a big data educator at Simplelearn.

Hilary Manson

She is a big data professional who manages multiple roles together. Hilary is a data scientist at Accel, Vice president at Cloudera, and a speaker and writer in this field. Back in 2014, she founded a machine learning research company called Fast Forward labs. Clearly, she is a big data analytics influencer that everyone should follow.

Carla Gentry

Currently working in Samtec Inc; she has helped many big shot companies to draw insights from complicated data and increase profits. Carla is a mathematician, an economist, owner of Analytic Solution, a social media ethusiat, and a must-follow expert in this field.

Vincent Granville

Vincent Granville’s thorough understanding of topics like machine learning, BI, data mining, predictive modeling and fraud detection make him one the best influencers of 2018. Data Science Central-the popular online platform for gaining knowledge on big data analytics has been cofounded by Vincent.

Merv Adrian

Presently the Research Vice President at Gartner, he has over 30 years of experience in IT sector. His current work focuses on upcoming Hadoop technologies, data management and data security problems. By following Merv’s blogs and twitter posts, you shall be informed about important industry issues that are sometimes not covered in his Gartner research publications.

Bernard Marr

Bernard has earned a good reputation in the big data and analytics world. He publishes articles on platforms like LinkedIn, Forbes and Huffington Post on a daily basis. Besides being the major speaker and strategic advisor for top companies and the government, he is also a successful business author.

Craig Brown

With over twenty years of experience in this field, he is a renowned technology consultant and subject matter expert. The book Untapped Potential, which explains the path of self-discovery, has been written by Craig.

If you have read the entire article, then one thing is very clear-you are a big data enthusiast! So, why not make your career in the big data analytics industry?

Enroll for big data Hadoop courses in Gurgaon for a firm footing in this field. To read more interesting blogs regularly, follow Dexlab Analytics– a leading big data Hadoop training center in Delhi. Interested candidates can avail flat 10% discount on selected courses at DexLab Analytics.

 

Reference: www.analyticsinsight.net/top-12-big-data-analytics-and-data-science-influencers-in-2018

 

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Step-by-step Guide for Implementation of Hierarchical Clustering in R

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Step-by-step Guide for Implementation of Hierarchical Clustering in R

Hierarchical clustering is a method of clustering that is used for classifying groups in a dataset. It doesn’t require prior specification of the number of clusters that needs to be generated. This cluster analysis method involves a set of algorithms that build dendograms, which are tree-like structures used to demonstrate the arrangement of clusters created by hierarchical clustering.

It is important to find the optimal number of clusters for representing the data. If the number of clusters chosen is too large or too small, then the precision in partitioning the data into clusters is low.

NbClust

The R package NbClust has been developed to help with this. It offers good clustering schemes to the user and provides 30 indices for determining the number of clusters.

Through NbClust, any combination of validation indices and clustering methods can be requested in a single function call. This enables the user to simultaneously evaluate several clustering schemes while varying the number of clusters.

One such index used for getting optimum number of clusters is Hubert Index.

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Performing Hierarchical Clustering in R

In this blog, we shall be performing hierarchical clustering using the dataset for milk. The flexclust package is used to extract this dataset.

The milk dataset contains observations and parameters as shown below:

As seen in the dataset, milk obtained from various animal sources and their respective proportions of water, protein, fat, lactose and ash have been mentioned.

For making calculations easier, we scale down original values into a standard normalized form. For that, we use processes like centering and scaling. The variable may be scaled in the following ways:

Subtract mean from each value (centering) and then divide it by standard deviation or divide it by its mean deviation about mean (scaling)

Divide each value in the variable by maximum value of the variable

After scaling the variables we get the following matrix

The next step is to calculate the Euclidean distance between different data points and store the result in a variable.

Hierarchical average linkage method is used for performing clustering of different animal sources. The formula used for that is shown below.

We obtain 25 clusters from the dataset.

To draw the dendogram we use the plot command and we obtain the figure given below.


The Nbclust library is used to get the optimum number of clusters for partitioning the data. The maximum and minimum number of clusters that is needed is stored in a variable. The nbClust method finds out the optimum number of clusters according to different clustering indices and finally the Hubert Index decides the optimum value of the number of clusters.

The optimum cluster value is 3, as can be seen in the figure below.

Values corresponding to knee jerk visuals in the graph give the number of clusters needed.

The graph shows that the maximum votes from various clustering indices went to cluster 3. Hence, the data is partitioned into 3 clusters.

The graph is partitioned into 3 clusters as shown by the red lines.

Now, the points are portioned into 3 clusters as opposed to the 25 clusters we got initially.

Next, the clusters are assigned to the observations.

The clusters are assigned different colors for ease of visualization


That brings us to a close on the topic of Hierarchical clustering. In the upcoming blogs, we shall be discussing K-Means clustering. So, follow DexLab Analytics – a leading institute providing big data Hadoop training in Gurgaon. Enroll for their big data Hadoop courses and avail flat 10% discount. To more about this #SummerSpecial offer, visit our website.

 

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Study: Demand for Data Scientists is Sky-Rocketing; India Leads the Show

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Study: Demand for Data Scientists is Sky-Rocketing; India Leads the Show

Last year, India witnessed a surging demand for data scientists by more than 400% – as medium to large-scale companies are increasingly putting their faith on data science capabilities to build and develop next generation products that will be well integrated, highly personalized and extremely dynamic.

Companies in the Limelight

At the same time, India contributed to almost 10% of open job openings for data scientists worldwide, making India the next data science hub after the US. This striking revelation comes at a time when Indian IT sector job creation has hit a slow mode, thus flourishing data science job creation is found providing a silver lining. According to the report, Microsoft, JPMorgan, Deloitte, Accenture, EY, Flipkart, Adobe, AIG, Wipro and Vodafone are some of the top of the line companies which hired the highest number of data scientists this year. Besides data scientists, they also advertised openings for analytics managers, analytics consultants and data analysts among others.

City Stats

After blue chip companies, talking about Indian cities which accounts for the most number of data scientists – we found that Bengaluru leads the show with highest number of data analytics and science related jobs accounting for almost 27% of the total share. In fact, the statistics has further increased from the last year’s 25%, followed by Delhi NCR and Mumbai. Even, owing to an increase in the number of start-ups, 14% of job openings were posted from Tier-II cities.

Notable Sectors

A large chunk of data science jobs originated from the banking and financial sector – 41% of job generation was from banking sector. Other industries that followed the suit are Energy & Utilities and Pharmaceutical and Healthcare; both of which have observed significant increase in job creation over the last year.

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Talent Supply Index (TSI) – Insights

Another study – Talent Supply Index (TSI) by Belong suggested that the demand in jobs is a result of data science being employed in some areas or the other across industries with burgeoning online presence, evident in the form of targeted advertising, product recommendation and demand forecasts. Interestingly, businesses sit on a massive pile of information collected over years in forms of partners, customers and internal data. Analyzing such massive volumes of data is the key.

Shedding further light on the matter, Rishabh Kaul, Co-Founder, Belong shared, “If the TSI 2017 data proved that we are in a candidate-driven market, the 2018 numbers should be a wakeup call for talent acquisition to adopt data-driven and a candidate-first approach to attract the best talent. If digital transformation is forcing businesses to adapt and innovate, it’s imperative for talent acquisition to reinvent itself too.”

Significantly, skill-based recruitment is garnering a lot of attention of the recruiters, instead of technology and tool-based training. The demand for Python skill is the highest scoring 39% of all posted data science and analytical jobs. In the second position is R skill with 25%.

Last Notes

The analytics job landscape in India is changing drastically. Companies are constantly seeking worthy candidates who are well-versed in particular fields of study, such as data science, big data, artificial intelligence, predictive analytics and machine learning. In this regard, this year, DexLab Analytics launches its ultimate admission drive for prospective students – #BigDataIngestion. Get amazing discounts on Big Data Hadoop training in Gurgaon and promote an intensive data culture among the student fraternity.

For more information – go to their official website now.

 

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The Power of Data: How the Industry Has Changed After Adding Data

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The volume of data is expanding at an enormous rate, each day. No more are 1s and 0s are petty numerical digits, they are now a whole new phenomenon – known as Big Data. A fair assessment of the term helped us understand the massive volume of corporate data collected from a broad spectrum of sources is what big data is all about.

A recent report suggested that organizations are expected to enhance their annual revenues by an average of $5.2 million – thanks to big data.

More about Data, Rather Big Data

Back in the day, most of the company information used to be stored in written formats, like on paper. For example, if 80% of confidential information was kept on paper, 20% was stored electronically. Now, out of that 20%, 80% was kept in databases.

With time, things have changed. Across the business domain, more than 80% of companies store their data in electronic formats nowadays, and at least 80% of that is found outside databases, because most organizations prefer storing data in ad hoc basis in files at random places.

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Now, the question is what kind of data is of crucial importance? Data, that impacts the most?

With that in mind, we’ve three kinds of data:

  • Customer Data
  • IT Data
  • Internal Financial Data

The Value of Data

For companies, data means dollars – the way data costs companies’ their time and resources, it also leads to increased revenue generation. However, the key factor to be noted here is – the data have to be RELEVANT. Despite potential higher revenues through advanced data skills and technology implementation, an average enterprise is only able to employ 51% of total accumulated and generated data, and less than 48% of decisions are based on that.

To say the least, unlike before, today’s organizations gather data from a wide array of sources – CCTV footage, video-audio files, social networking data, health metrics, blogs, web traffic logs and sensor feeds – previously companies were not as efficient and tech-savvy as they are now. In fact, five years ago, some of the sources from which data is accumulated did not even exist nor were they available on corporate radar.

With the rise of ingenious and connected technologies, companies are turning digital. It hardly matters if you are an automobile manufacturer, fashion collaborator or into digital marketing – being connected digitally and owning meaningful data is all to cash on. You can structure intricate database just with consumers’ details, both personal and professional, such as age, gender, interests, buying patterns, behavioral statistics and habits. Remember, accumulating and analyzing data is not only productive for your company but also becomes a saleable service in its own way.

Make Data the Bedrock of Your Business

Data has to be the life and blood of business plans and decisions you want to make. Ensure your employees learn about the value of data collection, make sure you align your IT resources properly and keep pace with the latest data tools and technologies as they tend to keep on changing, constantly.

Embrace the change – while physical assets are losing importance, data appears to be the most valuable asset a company can ever have.

For big data hadoop certification in gurgaon, look no further than DexLab Analytics. With the right skills in tow and adequate years of experience, this analytics training institute is the toast of the town. For more information, visit our official page. 

 

The blog has been sourced from:

https://www.digitaldoughnut.com/articles/2016/april/data-may-be-the-most-valuable-asset-your-company-h

https://www.techrepublic.com/blog/cio-insights/big-data-cheat-sheet/

https://www.techrepublic.com/article/the-3-most-important-types-of-data-for-your-business

 

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