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Big Data Could Solve Drug Overdose Mini Epidemic

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Big Data Could Solve Drug Overdose Mini Epidemic

Big data has become an essential part of our everyday living. It’s altering the very ways we collect and process data.

Typically, big data in identifying at-risk groups also shows signs of considerable growth; the reasons being easy availability of data and superior computational power.

The issue of overprescribing of opioids is serious, and over 63000 people has died in the United States last year from drug overdose, out of which more than 75% of deaths occurred due to opioids. Topping that, there are over 2million people in the US alone, diagnosed with opioid use disorder.

But of course, thanks to Big Data: it can help physicians take informed decisions about prescribing opioid to patients by understanding their true characteristics, what makes them vulnerable towards chronic opioid-use disorder. A team from the University of Colorado accentuates how this methodology helps hospitals ascertain which patients incline towards chronic opioid therapy after discharge.

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Big Data offers helps

The researchers at Denver Health Medical Center developed a prediction model based on their electronic medical records to identify which hospitalized patients ran the risk of progressing towards chronic opioid use after are discharged from the hospital. The electronic data in the record aids the team in identifying the number of variables linked to the advancement to COT (Chronic Opioid Therapy); for example, a patient’s history of substance abuse is exposed.

As good news, the model was successful in predicting COT in 79% of patients and no COT in 78% of patients. No wonder, the team claims that their work is a trailblazer for curbing COT risk, and scores better than software like Opioid Risk Tool (ORT), which according to them is not suitable for hospital setting.

Therefore, the prediction model is to be incorporated into electronic health record and activated when a healthcare specialist orders opioid medication. It would help the physician decipher the patient’s risk for developing COT and alter ongoing prescribing practices.

“Our goal is to manage pain in hospitalized patients, but also to better utilize effective non-opioid medications for pain control,” the researchers stated. “Ultimately, we hope to reduce the morbidity and mortality associated with long-term opioid use.”

As parting thoughts, the team thinks it would be relatively cheaper to implement this model and of great support for the doctors are always on the go. What’s more, there are no extra requirements on the part of physicians, as data is already available in the system. However, the team needs to test the cutting edge system a number of times in other health care platforms to determine if it works for a diverse range of patient populations.

On that note, we would like to say DexLab Analytics offers SAS certification for predictive modeling. We understand how important the concept of predictive analytics has become, and accordingly we have curated our course itinerary.

 

The blog has first appeared on – https://dzone.com/articles/using-big-data-to-reduce-drug-overdoses

 

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10 Key Areas to Focus When Settling For an Alternative Data Vendor

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10 Key Areas to Focus When Settling For an Alternative Data Vendor

Unstructured data is the new talk of the town! More than 80% of the world’s data is in this form, and big wigs of financial world need to confront the challenges of administering such volumes of unstructured data through in-house data consultants.

FYI, deriving insights from unstructured data is an extremely tiresome and expensive process. Most buy-sides don’t have access to these types of data, hence big data vendors are the only resort. They are the ones who transform unstructured content into tradable market data.

Here, we’ve narrowed down 10 key areas to focus while seeking an alternative data vendor.

Structured data

Banks and hedge funds should seek alternative data vendors that can efficiently process unstructured data into 100% machine readable structured format – irrespective of data form.

Derive a fuller history

Most of the alternative data providers are new kid in the block, thus have no formidable base of storing data. This makes accurate back-testing difficult.

Data debacles

The science of alternative data is punctured with a lot of loopholes. Sometimes, the vendor fails to store data at the time of generation – and that becomes an issue. Transparency is very crucial to deal with data integrity issues so as to nudge consumers to come at informed conclusions about which part of data to use and not to use.

Context is crucial

While you look at unstructured content, like text, the NLP or natural language processing engine must be used to decode financial terminologies. As a result, vendors should create their own dictionary for industry related definitions.

Version control

Each day, technology gets better or the production processes change; hence vendors must practice version control on their processes. Otherwise, future results will be surely different from back-testing performance.

Let’s Take Your Data Dreams to the Next Level

Point-in-time sensitivity

This generally means that your analysis includes data that is downright relevant and available at particular periods of time. In other cases, there exists a higher chance for advance bias being added in your results.

Relate data to tradable securities

Most of the alternative data don’t include financial securities in its scope. The users need to figure out how to relate this information with a tradable security, such as bonds and stocks.

Innovative and competitive

AI and alternative data analytics are dramatically changing. A lot of competition between companies urges them to stay up-to-date and innovative. In order to do so, some data vendors have pooled in a dedicated team of data scientists.

Data has to be legal

It’s very important for both vendors and clients to know from where data is coming, and what exactly is its source to ensure it don’t violate any laws.

Research matters

Few vendors have very less or no research establishing the value of their data. In consequence, the vendor ends up burdening the customer to carry out early stage research from their part.

In a nutshell, alternative data in finance refer to data sets that are obtained to inject insight into the investment process. Most hedge fund managers and deft investment professionals employ these data to derive timely insights fueling investment opportunities.

Big data is a major chunk of alternative data sets. Now, if you want to arm yourself with a good big data hadoop certification in Gurgaon then walk into DexLab Analytics. They are the best analytics training institute in India.

The article has been sourced from – http://dataconomy.com/2018/03/ten-tips-for-avoiding-an-alternative-data-hangover

 

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How Data Exhaust is Leveraged for Your Business

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How Data Exhaust is Leveraged for Your Business

Big data is the KING of corporate kingdom. Every company is somehow using this vital tech tool; even if they are not using it, they are thinking of it.

A 2017 survey says, around 53% of companies were relying on big data for their business operations. Each company focuses on a particular variant of data. Some of the data types are considered most important, while others are left out. Now what happens to the data that is kept aside?

Data exhaust can be a valuable addition for a company – if leveraged properly.

Let’s Take Your Data Dreams to the Next Level

Explaining Data Exhaust

It entirely deals with the data that is leftover but produced by the company itself. Keep in mind, when you try collect information from a specific set of data, a whole lot of information is also collected at the same time. So, many organizations might be sitting on a gold mine of data but without acknowledging the importance of that data. In instances like this, data exhaust can be very helpful across numerous business development channels.

Market Research

The best way to use data exhaust is through extensive market research. Know your audience is the key. Customers are crucial for effective marketing and product development. Nevertheless, the former involves manual research as well as analytical research, which once again leads us to analytics.

Through data exhaust, you get to know everything your customers do on your website – thus, can understand what they like better.

Cyber Security

As a potent threat, cyber crime results into potential costs to businesses all across the world. So, what role does data exhaust play? At best, it can help determine risk across different databases to develop superior cyber security plan.

Product Development

Importantly, businesses work on a plethora of projects at the same time. As a result, the issue of time crunch pops up. No one can do everything all at once, and data exhaust helps in sharpening whatever is important. Like, if your excess data says that most of your viewers visit your site through mobile device, it’s better to develop a mobile app to serve the customers better.

All Data Is Not Important

All data is not useful. Though data exhaust is useful, yet there would be times when you will come across bad data. You need to shed off those data, and get rid of data of that manner that is meaningless. Ask data experts which data to keep and which is irrelevant. Data that is of no use needs to be destroyed, because a company cannot keep trash for long.

Be Responsible for Data

Its clear data exhaust is all good and great for business, but it’s always suggestible to be cautious and responsible. There can be many legal implications, hence its suggestible to consult a data professional who have the desired know-how, otherwise things can get a bit complicated.

In this world of competitive technology, businesses have to be very careful about how they are using data to avoid any kind of negative outcomes. Be responsible and use data correctly; big data help frame a highly effective business strategy.

Looking for good big data courses? We have good news rolling your way – DexLab Analytics offers excellent big data training in Gurgaon. If interested, check out the course itinerary RN.

The blog is sourced from – http://dataconomy.com/2018/03/how-data-exhaust-can-be-leveraged-to-benefit-your-company

 

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Discover: Interesting Ways Netflix Relies on Big Data

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Discover: Interesting Ways Netflix Relies on Big Data

Netflix boasts of over 100 million subscribers – a humongous wealth of data is stored and analyzed to enhance user experience. Big data makes Netflix the King of Stream; it keeps the customers engaged and content.

Big data recommends Netflix a list of programs that interests the viewers and this system actually influences 80% of content that is available on Netflix. Estimates say the cutting edge algorithms save $1 billion a year in value from customer retention – undoubtedly, a whopping figure for the entertainment industry.

Big data is used extensively all through Netflix application, BUT the Holy Grail is the prediction part: what the customers want to watch and enjoy matters the most. Moreover, big data is the fuel that powers up the recommendation engines that are created to serve the purpose.

netflix-and-devices-243

Healthy prediction of viewing habits

Efforts started way back in 2006, when Netflix was primarily into DVD-mailing business. It initiated the Netflix prize, rewarding $1 million to any group, which can devise the best algorithm to predict how a customer would rate a particular movie, based on previous ratings. Today, though the algorithms are constantly updated, but the principles still remain a key characteristic of a recommendation engine.

In the beginning, analysts were left with very little data about their customers, but as soon as streaming became more mainstream, new data points about their customers became easily available. What affects a particular movie had on a viewer could be assessed, as well as models were built to predict the ‘perfect storm’ situation for customers who were served with the movies they like.

Infographic-Netflix-knows-when-youre-Hooked

Identifying the next smashing series

Of late, Netflix has broadened its scope to include content creation, instead of limiting itself to being a distribution method for movie studios and other channels. This strategy is of course backed by meaningful data – which highlighted how its viewers are hungry for content directed by David Fincher and starring Kevin Spacey.

Every minute part of the production of the series is structured on data, including the colors used on the cover image of the series to draw in subscribers.

Netflix

For a quality experience

Netflix takes the quality aspect into great consideration. It closely monitors and analyzes the various factors that affect user behavior. Even, it develops models to explore how they perform. While, a large number of shows are hosted internally on its own distributed network of servers, they are also reflected around the world by ISPs and other hosts. Along with improving the user experience, efficient content streaming reduces costs for ISPs – shielding them from the cost of downloading data from Netflix server.

Big data and analytics have positioned themselves in the right order to dictate the operations across all Netflix platforms. They surely lead the pack of data by taking over distribution and production networks and re-modifying them through constant evolution and innovation of data.

Not only this, Netflix has reduced its promotional campaign budgets by targeting only the most relevant and interested people at the same time. All possible because of big data.

So, next time, when you peruse through your favorite shows in Netflix, do think and thank the power of big data. Because, big data is much more than what you think!

DexLab Analytics, a renowned big data training institute in Gurgaon is the best place to start a big data certification endeavor. The consultants are proficient in what they teach, the course curriculum is comprehensive and flexible course modules are suitable for everyone, irrespective of professionals or students.

The article has been sourced from:                                 

https://insidebigdata.com/2018/01/20/netflix-uses-big-data-drive-success

http://dataconomy.com/2018/03/infographic-how-netflix-uses-big-data-to-drive-success

https://www.linkedin.com/pulse/amazing-ways-netflix-uses-big-data-drive-success-bernard-marr

 

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5 Steps to Reassess Your Big Data Business Strategy

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5 Steps to Reassess Your Big Data Business Strategy

Company employees at all levels need to understand the role of big data in planning business strategies. Strategic planning has to be dynamic- constantly revised and aligned with the current market trends.

As the first quarter of 2018 is nearing to its end, here are 5 domains every business needs to pay attention to:-

  • Information retention for field-based technology:

In the current tech-driven business world, a lot of information needs to be collected from field-based technologies, like drones and sensors. Owing to internet bandwidth constraints, this data has to be stored locally instead of transmitting them for collection in a central location. Bandwidth constraints affect cloud-based storage systems too. Thus, companies need to restore traditional practices of distributed data storage, which involve collecting data locally and storing them on servers or disks.

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  • Collaboration with cloud vendors:

Cloud hosting is popular among businesses, especially in small and midsized enterprises. Onsite data activities of companies include maintenance of infrastructure and networks that ensure internal IT access. With the shift towards cloud-based applications, businesses need to revise disaster recovery plans for all kinds of data. It should be ensured that vendors adhere to corporate governance standards, implement failover if needed, and SLAs (Service Level Agreements) match business needs. It is often seen that IT strategic plans lack strong objectives pertaining to vendor management and stipulated IT service levels.

  • How a company defines ROI:

In the constantly evolving business scenario, it is necessary to periodically re-evaluate the ROI (return on investments) for a technology that was set at the time of purchasing it. Chief information officers (CIOs) should regularly evaluate ROIs of technological investments and adjust business course accordingly. ROI evaluation should be a part of IT strategic planning and needs to be revisited at least once a year. An example of changing business value that calls for ROI re-assessment is the use of IoT technology in tracking foot traffic in physical retail stores. At a point of time, this technology helped managers display the most desirable products in best positions within a store. With the shift of customer base from physical to online venues, this tech has become redundant in terms of physical merchandising.

  • How business performance is assessed:

Like shifting ROIs, KPIs (key performance indicators) for companies that are based on inferences drawn from their data, are expected to change over time. Hence, monitoring these shifting KPIs should be a part of a company’s IT strategic plan. For example, customer engagements for a business might shift from social media promotions to increased mentions of product defects. Therefore, to improve customer satisfaction, businesses should consider reducing the number of remanufacture material authorizations and IoT alerts for sensors/devices in the production processes of these goods.

  • Adoption of AI and ML:

Artificial intelligence and machine learning play major roles in the current technological overhaul. Companies need to efficiently incorporate AI-powered and ML-based technologies in their business processes. Business leaders play key roles in identifying areas of a business where these techs could add value; and then testing their effectiveness through small-scale preliminary projects. This should be an important goal in the R&D strategic planning of business houses.

Let’s Take Your Data Dreams to the Next Level

As mentioned in Harvard Business review, ‘’the problem is that, in many cases, big data is not used well. Companies are better at collecting data-about their customers, about their products, about competitors-than analyzing the data and designing strategy around it.’’

‘’Used well’’ means not only designing superior strategies but also evolving these strategies with changing market trends.

From IT to marketing- professionals in every sector are going for big data training courses to enhance their competence. Enroll for the big data Hadoop certification course in Gurgaon at DexLab Analytics– a premier data analyst training institute in Delhi.

 

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How Big Data Plays the Key Role in Promoting Cyber Security

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The number of data breaches and cyber attacks is increasing by the hour. Understandably, investing in cyber security has become the business priority for most organizations. Reports based on a global survey of 641 IT and cyber security professionals reveal that a whopping 69% of organizations have resolved to increase spending on cyber security. The large and varied data sets, i.e., the BIG DATA, generated by all organizations small or big, are boosting cyber security in significant ways.

How Big Data Plays the Key Role in Promoting Cyber Security

Business data one of the most valuable assets of a company and entrepreneurs are becoming increasingly aware of the importance of this data in their success in the current market economy. In fact, big data plays the central role in employee activity monitoring and intrusion detection, and thereby combats a plethora of cyber threats.

Let’s Take Your Data Dreams to the Next Level

  1. EMPLOYEE ACTIVITY MONITERING:

Using an employee system monitoring program that relies on big data analytics can help a company’s human resource division keep a track on the behavioral patterns of their employees and thereby prevent potential employee-related breaches. Following steps may be taken to ensure the same:

  • Restricting the access of information only to the staff that is authorized to access it.
  • Staffers should use theirlogins and other system applications to change data and view files that they are permitted to access. 
  • Every employee should be given different login details depending on the complexity of their business responsibilities.

 

  1. INTRUSION DETECTION:

A crucial measure in the big data security system would be the incorporation of IDS – Intrusion Detection System that helps in monitoring traffic in the divisions that are prone to malicious activities. IDS should be employed for all the pursuits that are mission-crucial, especially the ones that make active use of the internet. Big data analytics plays a pivotal role in making informed decisions about setting up an IDS system as it provides all the relevant information required for monitoring a company’s network.

The National Institute of Standards and Technology recommends continuous monitoring and real-time assessments through Big Data analytics. Also the application of predictive analytics in the domain of optimization and automation of the existing SIEM systems is highly recommended for identifying threat locations and leaked data identity.

  1. FUTURE OF CYBER SECURITY:

Security experts realize the necessity of bigger and better tools to combat cyber crimes. Building defenses that can withstand the increasingly sophisticated nature of cyber attacks is the need of the hour. Hence advances in big data analytics are more important than ever.

Relevance of Hadoop in big data analytics:

  • Hadoop provides a cost effective storage solution to businesses.
  • It facilitates businesses to easily access new data sources and draw valuable insights from different types of data.
  • It is a highly scalable storage platform.
  • The unique storage technique of Hadoop is based on a distributed file system that primarily maps the data when placed on a cluster. The tools for processing data are often on the same servers where the data is located. As a result data processing is much faster.
  • Hadoop is widely used across industries, including finance, media and entertainment, government, healthcare, information services, and retail.
  • Hadoop is fault-tolerant. Once information is sent to an individual node, that data is replicated in other nodes in the cluster. Hence in the event of a failure, there is another copy available for use.
  • Hadoop is more than just a faster and cheaper analytics tool. It is designed as a scale-out architecture that can affordably store all the data for later use by the company.

 

Developing economies are encouraging investment in big data analytics tools, infrastructure, and education to maintain growth and inspire innovation in areas such as mobile/cloud security, threat intelligence, and security analytics.

Thus big data analytics is definitely the way forward. If you dream of building a career in this much coveted field then be sure to invest in developing the relevant skill set. The Big Data training and Hadoop training imparted by skilled professionals at Dexlab Analytics in Gurgaon, Delhi is sure to give you the technical edge that you seek. So hurry and get yourself enrolled today!

 

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How Data is Found Influencing Political Campaigns Online

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How Data is Found Influencing Political Campaigns Online

Data is and has always been the heart and blood of politics. In the 21st century, digital transformation has hit politics hard. Ambitious politicians and lobbyists invest hundreds of dollars on framing potential campaigns and agendas: in the past US presidential elections, as much as $5 billion dollars was spent, if not less, out of which estimated $1 billion was set aside for digital advertising alone.

Online information has already started weaving a change in perspective of people. They tend to manipulate us. Few are even of the notion that big data is being used to develop customized political advertising that challenges our rational minds and change our voting pattern. But do you think it’s true? Can data have that kind of intense impact?

Cambridge Analytica Data Breach

In the wake of Facebook and Cambridge Analytica data breach, where data of 50 million Facebook users were compromised, a compelling issue of data safety and protection has come to the forefront of our conscience. Cambridge Analytics is a British political consulting firm that works by integrating data mining, data analysis and brokerage with strategic communication for successful electoral processes.

A recent terrifying revelation suggested that this company has used Facebook users’ confidential data to predict personalities and then tailor personalized advertizing according to their psychological attributes. For years, this company has been performing data analysis services strategizing various presidential campaigns for US and UK. This March, the data analytics firm has been alleged to have harvested information from more than 50 million Facebook users without their knowledge to build a system for targeting US voters. The employees of the firm were also found boasting about using fake news, fabricated sex scandals and cheap tricks to swing electoral campaigns across the globe and this has created a big uproar in the industry.

From this, anyone can fathom the power of data in politics and framing opinions. Digital technologies have become a powerful tool for both positive and negative change. Technology remains remote, pivotal and paternalist. The political systems are changing, and so are we. That’s why it’s high time for all of us to be cautious, prudent and have a voice of our own.

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How to Enhance Online Campaign Success Legally

While social media scores high, email actually pulls the reigns, when it comes to raising funds for political campaigns online.

Mitt Romney’s 2012 campaign revealed about 70% donations came through emails.

During the Obama campaign, the figures were as high as 90% to be precise.

Besides raising funds online via email, integration of myriad digital marketing channels with smart data is crucial to rally in unconditional support on behalf of candidates.

Here are ways to boost your online campaign success:

  • Mobile ads – Increase relevancy for micro-targeted audience
  • Actionable TV – Using set-top-box information, particular demographics has to be targeted
  • Retargeting – Targeting should be focused on historical donors, interested in your policies
  • SEO decisions – Upload content suitable for the target audience and improve search rankings
  • Email messages – it would segment your lists while enhancing campaign results

To put simply, better data yields positive results for political campaigns, along with supporting fundraising, awareness and presence. However, remember, not all data is clean and safe and not all data providers are credible and honest. Watch the news, join the drive, but stay true to your opinions and insights. They will never fail you.

Get trained by the experts from DexLab Analytics on big data hadoop. It’s a premier data analytics training institute in Delhi NCR that offers incredible big data training to the students.

The article has been sourced from:

https://www.theguardian.com/commentisfree/2017/mar/06/big-data-cambridge-analytica-democracy

https://webbula.com/how-data-helps-political-campaigns-succeed

 

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How Data Analytics Is Shaping and Developing Improved Storage Solutions

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Technology has penetrated deep into our lives – the last 5 decades of IT sector have been characterized by intense development in electronic storing solutions for recordkeeping.

 
How Data Analytics Is Shaping and Developing Improved Storage Solutions
 

Today, every file, every document is stored and archived safely and efficiently – rows of data are tabled in spreadsheets and stored in SQL relational databases for smooth access anytime by anyone, of course the authorized persons. Data is omnipresent. It is being found in data warehouses, data lakes, data mines and in pools. It is so much large in volume nowadays, that it can even be calculated in something like a Brontobyte.

 

Information is power. Data stored in archives are used to make accurate forecasts. And the data evaluation has begun within a subset of mathematics powered by a discipline named probability and statistical analysis.

 

Slowly, this discipline evolved into Business Intelligence that further into Data Science. The latter is the most sought after and well-paid career option for today’s tech-inspired generation. Grab a data science certification in Gurgaon and push your career to success.

 

Big Data Storage Challenges and Solutions

The responsibility of storage, ensuring security and provide accessibility for data is huge. Managing volumes and volumes of data is posing a challenge in itself – for example, even powering and cooling enough HDD RAID arrays to keep an Exabyte of raw data tends to break the bank for many companies.

 

Software-defined storage and flash devices are being deployed for big data storage. They promise of better direct business benefit. Also, increasingly Apache Spark Hadoop or simply Spark is taking care of the software side of big data analytics. Whether your big data cluster is developed on these open-source architectures or some other big data frameworks, it will for sure impact your storage decisions.

 

Hadoop is in this business of storage for big data for quite some time now. It is a robust open-source framework opted for suave processing of big data. It led to the emergence of server clusters and Facebook is known to have the largest Hadoop cluster containing millions of nodes.

 
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Now, the question remains where and how you proceed with Hadoop – there are so many differing opinions about how you approach Hadoop clusters, at times it may leave you exasperated. For that, we can help you here.

 

With a huge array of data at play, we suggest to deploy a dedicated processing, storage and networking system in different racks to avoid latency or performance issues. It is for the same reasons, we ask you to stay away running Hadoop in a virtual environment.

Instead, implement HDFS (Hadoop Distributed File System) – it is perfect for distributed storage and processing with the help of commodity hardware. The structure is simple, tolerant, expandable and scalable.

 

Besides, the cost of data storage should also be given a look at – cost should be kept low and data compression features should likely to be implemented.

For Big Data Hadoop certification in Delhi NCR, drop by DexLab Analytics.

 
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The Takeaway

Times are changing, and so are we. Big data analytics are becoming more real-time, hence better you scale up to real-time analytics. Today, data analytics have gone way beyond the conventional desktop considerations – it has now become a lot more, and to keep pace with the analytics evolution, you need to have sound storage infrastructure, where possible upgrades to computing, storage and networking is easily available and implementable.

 

To answer about big data or Hadoop, power yourself up with a good certification in Big Data Hadoop from DexLab Anlaytics – such intensive big data courses do help!

 

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How Big Data Will Impact E-commerce Industry in 2018?

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Whatever happens online and offline, it’s because of DATA. As the technology evolves, the ways to gather and measure data also diversifies. The best way to grasp the data world mechanisms is to study and analyze trends in behavior.

 
How Big Data Will Impact E-commerce Industry in 2018?
 

Big data is a concentrated accumulation of conventional and digital data from within and outside company operations. The inception of big data has enabled businesses to use huge amounts of data to carry out bigger and more complicated analyses.

 

However, the pressing issue that people face today is that they have “too much” data – collecting, organizing and understanding data has become quite complicated because we now are inundated with ceaseless numbers, percentages, stats, facts and perceptions.

 

To be precise, for years, Big Data has been buzzing around the digital front – let’s delve into what it actually means and what promises it holds in 2018 for ecommerce…

 

E-commerce industries are the biggest consumers of data. They can extract any information from Big Data and predict customer behavior and streamline robust operations.

Here are 4 ways in which big data will change the shape of e-commerce in 2018:

Better shopper analysis

For online success, understanding shopper’s behavior is more than important. Harness big data; it offers information on trends, customer choices and spikes in demands. It is the key to successful marketing.

 

Throughout this year and more, big data analytics will continue tracking shopper behaviors and fine-tuning your marketing strategies based on that.

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Flawless customer service

 Figures regarding dissatisfied customers and frail customer service are alarming. Truly speaking, more than 90% of unhappy customers won’t like to do business with a company that has turned their expectations down, owing to poor customer service. Therefore, for ecommerce success, utmost focus on customer service is downright important.

 

This year, expect data analytics to improve customer experience, while giving more focus to predictive monitoring. This will aid companies in identifying crucial issues and resolve them before even a customer gets involved.

More secure and easy online payment options

Since big data came into our lives, several things, like online payments got easier and more secure. How?

 

  • Big data incorporates various payment functions in a single centralized platform. It helps in making the process easier, as well as reduces fraud risks.
  • The advanced analytics are powerful enough to identify threats and structure proactive solutions to combat potent risks.
  • Big data helps in detecting money laundering transactions.
  • Productive data analytics allows e-commerce chains to cross sell and upsell.

Mobile commerce evolution

Day by day, the use of smartphones is increasing. The use of desktop computers is soon becoming obsolete. Big data is making impossible things possible, especially in the world of smartphones and ecommerce. Companies can now very easily gather data from multiple sources and analyze customer trends through mobile technology. Google has pioneered a wave of technologies, giving preference to mobile friendly and highly responsive sites. They bring in higher traffic to their pages. Hence an instant hit!

 

As closing thoughts, ecommerce companies wholeheartedly thanks Big Data for the way it has simplified the process of online shopping. For more big data inspiration and blogs, follow DexLab Analytics.

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The article has been sourced from  –  http://dataconomy.com/2018/02/5-ways-big-data-analytics-will-impact-e-commerce-2018/
 

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