Even if we don’t know it, we are already an avatar. Not only if we are on social networks, we like to get lost in some massive game or travel to some metaverse to see a concert also because there is a profile of us on the network and in the hands of brands and companies that manage our data. Data that builds what we could call a personal Digital Twin in an automated way.

The Digital Twin concept, very much in vogue metaverse, is a reality that has allowed us to clone ourselves and become an unconscious avatar full of data. Including the long-awaited behavioral data: remember the deployment of Amazon in its behavioral targeting mechanics on the web and with Amazon Go: finally, it obtains behavioral data from the retail public in physical reality.

The need to see this consumer in terms of data has a lot to do with the arrival of Internet 2.0, where the social and personalized component became clear and demanding. In that web 2.0. marketing assumes the reality of a mass interpersonal medium, with the ability to communicate with hundreds of thousands of people but attending to their personalized tastes and contacting by name and surname. Getting quality leads without often knowing what to use certain data for is now a necessity with a real objective: to understand to better connect with the consumer.

Understanding the consumer is more necessary than ever, not only to discover their needs, and unfortunately also their weaknesses, but to be able to form part of their lifestyle, and without prioritizing the interest for the obvious business interest (which must be having it…), if not also assuming care, responsibility for their rights and making them participate in our purpose (the one that gives us meaning beyond exponential profit).

Under the premise of social and cultural capital and the existence of Big Data and our potential avatar, we discovered that the relationship experience must be personalized. It is no longer worth deciding our public with demographic, biological, or class data. In its day, it is here to stay: the lifestyle. It is the key to accessing the new hybrid consumer.

And Lifestyle-Centrism Prevailed

The lifestyle-centric concept, which prevails over the traditional product-centric, user-centric, or brand-centric strategic vision, allows us not to think of generation X but of a spectrum of the public committed to their lifestyle. Life, looking to see if they like sports, if they are a fan of the opera or if they have children, with what that entails. Whether it’s someone from X, Z, Millennials, or the “victims” of the Babyboom.

Attending a lifestyle means assuming a strategy related to the intimate and the human with the community. It is not worth a machine-building an automatic avatar from its collected data without sensitivity. It is about that we can personalize, and we must look with the eyes of those who have a human in front of us like this—design with a human-centric vision.

To undertake human-centric connection and creativity exercises or to propose a human-centered design, it is necessary to assume that the public is divided into layers, like the design of a website or onions. And in total, I have detected six layers, although it is likely that these will increase or merge or evolve.

The Public 6.0

The target audience seems to have six layers. Each person has six layers. Six vertices allow you to aim sensitively and efficiently when you have to innovate or make decisions for the future and count on your attention and trust. We are a person, citizens, consumers, spectators, workers, and avatars.

The first essential is that the target… is a person as is and without further pretensions. He is a person with his fears, insecurities, vocations, strengths, possibilities, and the long etcetera that life provides. For example, when you design intelligent voice devices, you soon come to the need to build a virtual personality. Because it is the personality, especially the voice, the moment we make a relationship construct and imagine who we are talking to, even the terrible biases arise. But that’s what there is. The Metaverse, if we think about it, will be much more effective to the ear than to the eye. But that is another topic.

The second layer of our public is that it is a citizen. Share space and live with other people, seek refuge, have decision-making capacity, and currently even cancel. You have rights but also responsibilities, and your ideas become a differentiating element while being the engine that makes the society in which we live possible.

The third layer is that we are consumers. It is evident that regardless of the political system we live in, consumption is a reality, from necessities such as water and food to the desire to appear to be riding around in a sports car. If we look around, everything is relativized towards consumption.

Within consumption and attending to the trend of the Metaverse and the challenges of marketing departments increasingly in need of attention and brand visibility in search of “love,” we soon realize that an essential layer for our platforms to work, campaigns, and messages are that he is also a spectator. We need to disconnect, that we love to have a good time. 

There is another layer that usually goes unnoticed and that by default is essential in our lifestyle: work, those who can are workers. We spend more time in the office, thinking about work or interacting with colleagues than living experiences with friends or enjoying family. That is why the culture in the company goes beyond making a purpose possible or launching innovation processes. It is also a care and encounter because we talk about talent and collaboration.

And last, but increasingly important, is the final layer in our hybrid reality. We are avatars. Whether we like it or not. We are amazed by the new superpowers, such as ubiquity or multitasking or digital shopping 24/7, just as we are amazed when we discover that we already exist in the virtual-digital even though we don’t know it or don’t want to. There is already a personal digital representation in the form of an avatar that is now open to us so that we can adopt and adapt it. Make it ours and include it in our lifestyle.

There are six layers to facing a more demanding, informed public that asks more than ever for us to get to know them but not spies on them. That calls for a more transparent, collaborative relationship where biased foundations of what we want, desire, or need are not taken for granted.

Suppose we want to design, create or plan and assume a human vision. In that case, I am afraid we will have to start by generating trust, attending to the different layers without isolating them, and, above all, demanding the sensitivity that we ask for ourselves. We need a human-centered communication that allows us to leap to new spaces such as the Metaverse, access audiences unthinkable until now for our brands, or build a real long-term relationship in a hybrid world full of uncertainties. No more, no less.

The post The Hybrid Public? appeared first on TechReviewsCorner.

Since the beginning of the online marketing of digital campaigns have sought to focus their communication efforts on niche markets that most interest them. In other words, the messages are focused on the brand’s target audience. But how to find it in a space as big as the Internet? Microtargeting offers the solution.

The Help of Big Data

It is not a secret that every time we carry out a certain action on the network, data is generated that is collected in a large database, called Big Data. This information is extremely valuable for companies since they can perfectly know their target with it. In this way, they make sure to adapt to the needs of each user, giving them what they need or demand.

Micro-Segmentation Tailored To The Consumer

We aim to collect the maximum information from those audiences that interest us and divide it into micro-segments. This strategy is especially useful for companies with several different audiences and wants to reach them directly. In this way, we can create fully personalized and related information and messages. This is vital to improve the company’s positioning and become a trusted brand for the consumer.

The Advantages of Microtargeting

This methodology effectively establishes a speech according to what the target audience needs. It is also especially useful for e-commerce since it lets them know which products or sections of the web attract the most attention and which go unnoticed.

In short, microtargeting will allow you to narrow down your messages by targeting your true target audience exclusively in a precise way through the design of messages in which it is reflected. Thus, we manage to generate a value proposition that will give a stable, secure, and lasting relationship over time.

When using this tool, companies must use it with caution and respect for the consumer to not feel restricted in terms of freedom or space.

Also Read: What Is Big Data? And Why Is It Important?

The post What Is Microtargeting? appeared first on TechReviewsCorner.

Simply put, “big data” is a term which refers to large or complex data sets of information that need processing and managed by analytical tools. This data can originate from a diversity of sources, such as cameras, sensors, and log files.

Perhaps a good example of big data being processed is by what can be considered the largest project in the world producing masses of data, the CERN project in Europe. Collecting enormous amounts of data produced by the particle collider, this information is automatically collated and sorted by advanced analytics software and artificial intelligence, syphoning off relevant and “important” information to be analysed by human scientists. Without the use of data analytics, it would be impossible to analyse all this data by humans alone.

Big data in construction

Big data is now being used by the construction industry to maximise efficiency and productivity. With the use of data analytic software tools, large amounts of information can be sorted and extracted from data repositories and made easily accessible to all those that need it, like contractors, architects, engineers, clients, and investors. This can help stop data wastage, like the reported approximate 96% of construction and engineering data that went unused in 2018.

Organising and budgeting

Analytics tools can be useful to construction teams by compiling data from previous and present construction projects and helping them anticipate potential delays as well as conceptualise the project timeline. The data can also be analysed to predict costs for things like materials and equipment hire, factoring in materials price increases like we have seen during the pandemic. This will help project managers better manage costs and prevent them from going over budgetary constraints; it will also help avoid any unanticipated extra costs. 

Design process

The construction industry is increasingly using digital tools like building information modelling (BIM). This allows for real time information and 3-D modelling so that all members of the team can access and input recommendations or changes, something that requires big data to be able to achieve this. Along with the use of AI, these digital tools require big data input to work. These advanced digital models are used as a predictive tool to flag up any potential issues before the construction work on the ground commences, potentially saving time and money. Moreover, any changes made can be relayed to all stakeholders in real time.

Construction work

Project management software is increasingly being used by construction workers to help analyse the mass of data and make better decisions. Once the data is analysed, it can produce automatic alerts sent to team members on potential issues and make necessary changes to schedules, which are then passed for assessment and collaboration. Team members can input data such as recommendations or ideas that can be accessed in real time by all those on the collaborative network.

As well as improving productivity and reducing costs, this software can potentially spot talent in the team as they are given free access to voice their ideas and opinions on project changes. 

Maintenance

Even after the construction phase is completed, the big data collected can be useful to the owners of the newly constructed building as this information can be used in the operation and maintenance of the building. Information gathered, for example, can help guide future renovation work and maintenance workers.
It’s possible that some builders will install and integrate sensors into the building so that things like structural conditions and temperature patterns can be permanently monitored, useful information for keeping a building well maintained and serviced.

Benefits of big data analytics

The benefits to industry from adopting big data are many and these include the following:

• Better strategic decisions

• Improved operations

• Greater customer insight

• Reducing costs

Building efficiency

Up to 35% of construction costs can be down to material waste and remedying mishaps, something that is only likely to increase with the rising costs of building materials and supply chain issues, like we are currently witnessing. With the use of data analytics, this cost can be mitigated by reducing construction time and material costs, which is achieved by early flagging of potential structural issues before labour and materials have been committed. The likelihood of human errors, therefore, can be reduced.

Environmental impact

It’s common knowledge that the construction sector holds the unenviable reputation of being a major environmental polluter. The production of cement, steel, and other materials is all energy-intensive and emits high levels of carbon. So, any reduction in the environmental impact is very welcomed.

The use of big data can help alleviate this problem by leveraging data from past projects and providing more accurate estimates of the required materials and energy for a future project. This will help mitigate wastage in materials and other precious resources. Not only will this save on wasting materials, but it will also reduce waste going to landfill sites.

Also Read: What Is Big Data? And Why Is It Important?

The post Why is Big Data Merging with the Construction Sector? appeared first on TechReviewsCorner.

More and more technologies and programs process these mountains of data and allow companies to benefit from advanced and data-based analyses.

What is Big Data?

Big data essentially describes two aspects: on the one hand, the term describes faster-growing amounts of data ever. On the other hand, it is also about new and compelling IT solutions and systems to work profitably. Especially data from z. B social networks make up a large part of this amount of data.

Big data is often used as a collective term for modern digital technology. In digitization, big data is increasingly influencing the collection, management, utilization, and, above all, digital data analysis.

Why is Big Data So Important?

Big data starts where conventional approaches to information processing reach their limits. Big data is, of course, also about the amount of data a company collects, but much more about what is ultimately done with it.

One of the primary goals is to discover reproducible business patterns. The correct use of data enables costs to be reduced, time to be saved, new products to be developed, offers to be optimized, and well-founded business decisions to be made. Users can do the following tasks more efficiently, among others:

• recognize fraudulent behavior in good time,
• Recalculate risk portfolios within a few minutes,
• foresee possible future events and results,
• Determine causes of problems, defects, and malfunctions almost in real-time,
• create vouchers based on customer buying habits.

Data Mining

As already described, the real added value of big data lies in the evaluation – also known as data mining. This term summarizes the entire process of preprocessing, searching, and evaluating data – i.e., the systematic use of methods for analysis with the aim of pattern recognition.

From a technical point of view, algorithms are used in data mining that helps to establish connections between the amounts of data and thus to discover cross-connections and trends. It is essential here: Data mining is only about the evaluation and not about the generation of new data.

Competitive Advantage With The Help of Big Data

Due to the enormous amounts of data that arise within a company, those responsible have entirely new insights into customers’ interests and behavior. Companies use analysis methods to filter and process this information. These methods provide insightful information about the customer – hidden patterns, unknown correlations. In this way, companies generate competitive advantages over their competitors.

Therefore, advanced data management is the prerequisite for process optimization since providing information in real-time is the basis for entirely new business processes. In addition, the growing technical possibilities offer companies the opportunity to use big data projects to simplify the system infrastructure and reduce the number of databases.

Software Tools For Analysis

There are several different software tools for analysis. One example of this is predictive analytics from SAP. The software uses big data for predictive analysis. Users get a forecast of future events and likely results based on the analysis of historical data. The software thus creates added value for companies, as decisions in every conceivable area can be made more well-founded based on forecast models.

This method is used for. B. in maintenance. To make predictions, large amounts of data are collected, stored, and analyzed. Storage and analysis technologies from big data, such as data lakes and analytical databases, are used.

The basis for predictive maintenance are systems that are equipped with sensors and networked, embedded systems.

Also Read: How Long Does It Take To Make Money From Blogging?

Big Data Use Cases

As described in the previous example, there are already areas in which big data is used. We have put together a selection of other fields of application here:

• Retail: In retail, using big data is key to building customer relationships. Retailers need to know what is most likely to appeal to their customers, which products which target group is buying, and what effective customer acquisition strategies are. Big data analyzes forms a reasonable basis for implementing this.
• Health care: In the health care system, accuracy, but also speed, are the top priorities – and in many cases also sufficient transparency to meet the strict legal requirements. With the help of efficient, extensive data management, healthcare providers can gain the knowledge they need to improve patient care.
• Banking: Because of the large amounts of information, banks have to find new, innovative ways of handling large amounts of data. Minimizing risk and fraud in compliance with legal regulations is as important as a positive customer experience and satisfied customers.
• Education: With the help of big data analytics, educational institutions can improve systems and curricula. This means that better systems for evaluating and supporting teachers and managers can also be implemented.
• Sales and Marketing: Big Data makes it easier for the sales and marketing departments to tailor product offerings to customer segments or individual customers and thus minimize losses in the customer base. The observation of the market and competition can therefore be expanded significantly with big data analyzes.

Conclusion

Big data will develop into a critical business success factor in the future. Therefore, it is already crucial for companies to take the time to collect, store, and process big data. Do you have any questions about big data or possible big data tools? Then we can help you. The mind square consultants are experts in the field – contact us, and we will be happy to advise you.

The post What Is Big Data? And Why Is It Important? appeared first on TechReviewsCorner.

CLOUD STORAGE WILL BECOME THE NORM WITH INCREASED SPEEDS

Currently, many businesses and individuals are still not taking advantage of cloud storage and its benefits. Data stored on good old internal hard drives, USB drives, or internal servers remains the norm. Why? Quite simply because the files are often too heavy to be transferred without latency from a remote server to the end-user. In question, the too low speeds offered by 4G and the little usable bandwidth.

Thanks to 5G and the considerable increase in transfer speeds, cloud storage, which presents unparalleled advantages, will become widespread. Where it took several minutes to download a huge video file with a 4G connection, you will be able to access most of your documents stored in the cloud in just a few seconds with 5G. As if these were held in the internet memory of your device. 5G theoretically makes it possible to reach speeds 100 times greater than those of 4G, or the order of 10 Gb / s

5G will, therefore, literally explode the demand for cloud storage. Whether for companies or individuals. As long as you have a reliable and fast connection, it is not conceivable to keep your data on internal storage (or at least keep it on internal storage without cloud backup in parallel). The risk of data loss is too significant in the event of a device failure, loss, or theft. And in addition, mobility access via the cross-device is not possible.

Also Read: How 5G Will Serve Marketing And Customer Experience

THE MOBILE VIDEO GAME INDUSTRY WILL DEMOCRATIZE CLOUD-GAMING

In addition, the video game sector will change considerably with the arrival of 5G. In particular, that of video games on mobile. Currently, if you want to enjoy a game on your smartphone or tablet, you need to download the content first. However, the latter’s weight continues to increase (and much faster than the storage capacity of our mobile devices).

The publishers who will set up cloud gaming will differentiate themselves considerably from the others and have a clear competitive advantage. Indeed, cloud gaming makes it possible to:

• Play any game immediately, without having to download any content first.
• Benefit from a constantly updated game
• and using the resources of a remote server much better than those allowed by our smartphones and tablets.
• Resume on your mobile device, without latency or visual difference, and a game started on your living room console or computer.

In short, you will understand, 5G is likely to revolutionize the video game industry. Sony, for example, has already understood this with the recent introduction of remote playback (the Playstation Remote Play). This feature allows you to stream any PS4 or PS5 game on all existing devices with the use of VPN for example privacyonline (mobile or not).

5G WILL ALLOW ARTIFICIAL INTELLIGENCE TO TAKE OFF

5G will also make it possible to strengthen real-time data processing capacities considerably. Crucial for developing artificial intelligence in mobility, 5G will allow the multiplication of communications between machines (what is called M2M ). And the processing of all this data will not be done 100% of the time locally. Indeed, most of the calculation operations will be carried out in the cloud on remote servers.

Thus, autonomous cars, intelligent urban equipment, etc., will be connected and will exchange a plethora of information thanks to the almost zero latency of 5G.

I think you will understand, and we are at the dawn of a real digital revolution. Some experts even speak of the fourth industrial revolution as the fields of applications are numerous and sometimes even still unknown. So, ready for this (r) evolution? Anyway, it has already started, and we are only at the very beginning!

Also Read: Wi-Fi 6 Or 5G: Which One Is Better?

The post How Will 5G Revolutionize The Cloud & Big Data? appeared first on TechReviewsCorner.

The End of Experimentation

Over the last few years, industries have been largely experimenting with AI/ML to find out how best to use it. As the technologies become more accessible, experimentation is gradually coming to an end. Healthcare, transportation, finance, and manufacturing brands alone are already moving past the experimentation stage and have adopted mass-scale adoption in a variety of different ways. SME brands in all sectors should be watching those bigger business models and taking note. The potential for ML and AI to level the playing field is just as impactful as social media was for marketing. That means that despite the inherent challenges, even the smallest of enterprises will be able to compete with the big names through the right applications of AI and ML.

Finding Team Members

One of the problems for business owners is that hiring tech specialists can be very challenging. That’s always down to a lack of understanding of what skills to look out for and the kinds of training applicants should have to perform AI/ML-related functions. That’s where research is going to come in. Tech buzzwords on a resume can look impressive, but without understanding what those terms mean, they can quickly lead to hiring mistakes that hold a company back from growth. While you should look for potential new employees with practical experience in AI and ML, formalized qualifications can be a lot more advantageous to watch for. Look for those applicants with Azure Machine Learning Studio training and who have used that training practically. The more you know what AI and ML can do for you, the easier it will be to fine-tune the relevant skills, training, and experience that you should be looking for.

Metadata – The New Gold

Big data has been called the ‘new oil’ for the last few years in almost every tech-related opinion piece and trend-spotting article. While the value of big data is indisputable, it’s metadata that will be joining the dots between big data and machine learning output. Labeling metadata is becoming the norm and is going to result in SMEs being better able to streamline those everyday business tasks and processes. One of the key challenges of big data is gleaning actionable insights from it. ML and AI are set to make big data more accessible, easier to read, and easier to action via labeled metadata that can transform any SME’s future.

Artificial intelligence and Machine Learning are not sci-fi concepts any longer. They are accessible technologies that even the smallest business models can leverage into high-value tools. As a result, they will only become more visible in workplaces around the world.

The post What SMEs Need to Know About AI and ML appeared first on TechReviewsCorner.

A correct use of Big Data is a fundamental tool to grow an eCommerce channel. And, in order to manage the large amount of data available and to be effective for the operation of electronic commerce, it is necessary to focus on the circle of competition and on the way the world works, taking into account an unpredictable context and having the necessary adaptability.

Today, in the e-commerce market, there is fierce competition and less customer loyalty to the brand. Therefore, it is necessary that eCommerce is constantly looking for new ways to retain customers, as well as to improve their experience.

Electronic commerce is agile and allows the possibility of reaching a global market. In this sense, as mentioned, it is key to operate within the previously established competition circle with the aim of taking advantage of its experience to amplify its production. The correct use of this knowledge of the market can entail a greater benefit than that which acts outside its circle, using the same level of effort.

The importance of Big Data

Through Big Data analysis it is possible to reveal patterns and trends in consumer behavior, allowing a series of decisions to be made based on these data; however, less than 0.5% of the available data is used for this purpose.

A BARC study points out, as some of the benefits that can be obtained from the use of big data, better strategic decision-making (69%), better control of operational processes (54%), a better understanding of the customers (52%) and cost reduction (47%).

Likewise, that eCommerce that is driven by data analytics, measure and enhance buyer analytics, customer service, customer experience personalization, provide a more secure online payment process and enhance targeted advertising.

Use of Big Data

Through data analysis, a consumer analysis can be carried out, preparing their profile, and reflecting their preferences and buying habits, which will allow improving eCommerce operations and even reveal unexpected purchasing behaviors.

Also, keep in mind that customer service plays a very important role in electronic commerce. In this sense, 71% of online customers expect to access the online help service in five minutes. In addition, it must be taken into account that 13% of customers who are not satisfied will transmit their opinions and / or feelings to a minimum of 15 people; while, if their experience is positive, 72% will share it with at least six people. For their part, online retailers can use Big Data to analyze the customer service experience, detecting the speed of their response times, as well as identifying and solving potential problems before the customer gets involved.

The post Big Data – An Essential Tool To Boost eCommerce appeared first on TechReviewsCorner.

That’s why companies try to offer an engaging and helpful customer service experience in every respect. With the evolution of technologies like artificial intelligence, Big Data, and blockchain, the customer service experience has evolved and improved a lot. These technologies offer companies a deep understanding of the latest trends and consumer behavior.

Gartner was already advancing in 2011 that, this same year 2020, 85% of customer interactions would be managed without involving a human being. Now, people don’t have to depend on humans to make purchases or contract services because applications make that task easier. The bots, without going any further, can solve many commercial questions without the need to contact customer service or support personnel.

The customer experience needs these technologies, especially in terms of Big Data and AI treatment, because the amount of data grows exponentially almost every day that passes, but also because customer expectations have grown significantly.

Analyzing and maintaining a large volume of data and, at the same time, providing customer-centric solutions are the fundamental reasons why the call center industry is turning to automation to improve and enhance the customer experience.

Here are some of the ways AI technologies can be used with Big Data to improve the customer experience:

• Improve the customer experience through chatbots and virtual assistants powered by AI.
• AI is effectively using predictive personalization to improve the user experience. By incorporating this predictive personalization into the daily life of consumers, it becomes more effective, in turn.
• There are tools such as facial recognition software, text analysis, and machine learning that can be used by companies to know what their customers are seeing at any given moment, determine the appropriate messages or how to communicate them at the ideal moment, and all in real-time.
• Visual analysis of customers and their expressions, along with analysis of text and feelings through voice, helps companies gauge emotions to lead to a different type of communication.
• These technologies support data-driven, real-time decision making.

This trend will only advance, and the constant developments in the field of emotion processing will bring about a real revolution in the medium-term customer experience.

The post Big Data and AI are Transforming The Customer Experience appeared first on TechReviewsCorner.

We are in the perfect moment to exploit this technology that offers great analysis capabilities. Accumulating and analyzing historical data is essential for the further development and implementation of business strategies appropriate to our clients and sector.

Despite being a technology that offers great advantages for business development, there are still certain barriers such as mistrust in data security that prevent the development of this solution in companies.

How can we build trust in Big Data? We must make companies see that:

1. Data exploration. It is the best way to find, visualize, and understand large amounts of data.
2. Consolidation and deregistration of applications. Big Data allows you to leave behind old data applications and change them for new ones that allow you to manage and integrate information in a more efficient and operational way.
3. 360-degree view of the consumer. It allows us to see the client in a unified way, that is, complete information about him.
4. Analysis of operations. Analyze the data for better business results, reducing costs, and increasing profits.
5. Increase data storage. By integrating Big Data with storage functionalities ( Cloud ), it increases the operational efficiency of companies.
6. Security and compliance. Data protection improves its integrity, mitigates risks, and reduces compliance costs.

In the not too distant future, the client will benefit from the use of Big Data by companies since, thanks to the analysis of their tastes, hobbies, wishes … companies will be able to offer products suitable to their needs and preferences.

The post Big Data As A Fundamental Element In Business Strategy appeared first on TechReviewsCorner.

What Will Big Data Affect?

Managing that multitude of data, called Big Data, today is key to the business future, the professional most wanted by HR: the data analyst.

In fact, it is perhaps one of the professions with the most job opportunities at the moment, which is accessed from multiple sectors, ranging from engineers to economists.

However, Big Data not only brings with it the need to hire specialized personnel, but the software developed for the management of big data is already a fundamental tool of HR. This tool has a surprising capacity for adaptation to the environment and is capable of predicting, selecting and promoting the actions to be carried out by the entire company, from training to the organization.

Predictive Software

They are tools that cross millions of data and generate reports taking into consideration a multitude of points of view.

Tomorrow’s employee will fit even in the most concrete both in the group and for individual projects. Big Data is expected to roll out soon to all big companies, in fact, those companies that won’t roll out in the coming months may be looking to an uncertain future.

Big Data Professional Requirements

• Data professionals or scientists must have knowledge of analysis, computing, and modeling.
• They must be able to communicate correctly with the managers of the companies since it will be necessary to identify the business problem and find the best solution.
• On the other hand, they are required to be skillful in preparing explanatory reports of the data, in order for the organization to make decisions.
• Professionals in this sector must be constantly evolving since Big Data is quite different from the traditional analysis system.

Recruit Big Data Professionals

• In order to manage these programs, it is important to have specialized registration and analysis personnel, capable of structuring the data and then interpreting them. In addition, the treatment of information must respect the privacy and data protection laws and not make improper use of them.
• In short, having specialists in the implementation of Big Data in business can make a difference, today and increasingly, in the development and optimization of companies.

Also Read : Artificial Intelligence To Fight Fraud

The post Employment In The Big Data Era appeared first on TechReviewsCorner.