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Do Big Data and Data Analytics Outweigh Standard Human Judgment? (Rank Princess)

Do Big Data and Data Analytics Outweigh Standard Human Judgment?

Big Data or a large mass of complex, diverse, heterogeneous information; challenges traditional data processing methods. As a result, it questions the capability of human judgment to analyze a large body of data. So, do Big Data and Data Analytics outweigh standard human judgment?

Some of the applications of Big Data in daily life:

• Predictions made by Google while searching for things using the search engine. Google analyzes the accumulated data based on the previous queries on similar subjects.
• Intimations from debit/credit card companies about unsolicited activities based on findings from millions of transactions every day.
• Different companies take online surveys for gathering data about their clients. The resulting data is used to predict customer requirements.
• Data analytics based on the medical history of patients can help doctors in predicting patients’ responses’ to drugs and aid in finding possible cures to diseases.

Impossible for humans to process Big Data manually

Judgment making abilities of human beings are inadequate to deal with Big Data. Information of such an enormous size and complexity cannot be analyzed by our brains.

Helping people make better informed decisions

Human beings may be inefficient in analyzing Big Data but the outcomes of data analytics by computers can help them achieve meaningful conclusions. The development of algorithms for advanced data analytics is likely to lead to social, economic and political development.

Benefiting people through Big Data

• The Management of organizations’ could become more transparent and increase workforce efficiency.
• Data analytics will offer a greater scope for performance-related experiments.
• Categorization of a population for customized results.
• Automated algorithms for effective inferences.
• Customized services will increase profitability in business.

Some drawbacks of Big Data and data analytics

Too much dependence on Big Data can lead to false confidence leading to errors in judgment. Ruling out human judgmental powers will allow powerful people manipulate findings and satisfy their interests.

Dealing with data analytics in a positive manner

In today’s world, it is beyond doubt that we need computer-generated data analytics for processing of large information. That does not necessarily mean a complete elimination of the standard judgment skills of human beings.

Data analytics and human judgment should complement each other

The results from analytics can complement human judgment for making important decisions. This realization has inspired multiple scientists across the world to look for new methods of data analytics for quick effective results.

Need for storing large data

Effective storage and data processing of Big Data can generate wonderful results. Data processing can help determine the causes of failures. It can help identify defects. It can increase business by analyzing buying habits of customers. It can also help organizations detect fraudulent behavior.

In order to get important results and their subsequent utilization, there cannot be a rivalry between Big Data, data analytics, and standard human judgment. Making do without any kind of human judgment is currently out of the question. Ruling out standard judgment can create misleading conclusions. On the other hand, data analytics and human judgment can together reap beneficial results.

Primary keyword – Big Data

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Improving Marketing with Conjunction of Big Data and Thick Data (Rank Princess)

Improving Marketing with Conjunction of Big Data and Thick Data

In the last ten years, the world witnessed an increasing shift towards online business. As online retailers offered lucrative opportunities, consumers began to prefer the convenience of digital purchasing.

Sharp incline in digitization let to a huge influx of customers. This led to a stiff competition between various merchants. Numerous marketing strategies came into force to lure people towards their brand. And with this came the need to manage and utilize Big Data.

What exactly is Big Data and how important it is in the world of digitized marketing?

Big Data is any huge set of data which is beyond the capability of the usual databases used for sorting and relating data. For the past five years, Big Data has been the Big word. It’s been sought after like a pack of wolves. From small businesses to large, everyone wants to gain advantages by compiling, sorting and analyzing huge data.

Data analytic tools are used to find correlations and patterns between vast data extending up to zettabytes, which is not humanly possible. Different data mining and predictive analysis tools, optimization and mathematical algorithms are deployed to get the relevant details. These are then used to derive important trends and make ground-breaking decisions.

Where and how does Thick Data come into the picture?

What lacks in Big Data is that is it too technical. Since trade is solely client-centric, it becomes imperative to understand their needs and expectations. No amount of mathematical curves or principles can precisely predict the unpredictable human behavior.

This is where Thick Data comes into the picture. Thick data essentially bridges the gaps in Big Data. Where Big Data is quantitative, Thick Data is qualitative. It aims at understanding the emotional quotient of the consumers. Thus probing at the dynamic human behaviors and draws conclusions over what and when customers are most likely to make their purchases.

Amalgamation of Thick Data into Big Data

Thick Data takes quantitative data from Big Data and incorporates it into the evolving human approach. This helps organizations develop customer-centric methods and build positive relations with them.

A short example would be the decline in sales of Lego Toys which led them to conclude that kids were not interested in building toys anymore. A further human-level assessment, in the form of spending time with kids playing Lego, proved that there are some who enjoy building Lego blocks while some don’t. They are all different with separate needs.

Marketing with the union of Big Data and Thick Data

There are some methods employed to tackle the merger of Thick Data into Big Data :

• Exploratory Data Analysis (EDA) – By exploring the compiled data specific undiscovered features are detected.

• Confirmatory Data Analysis (CDA) – This confirms the existing stats to be true or false based on human actions.

• Qualitative Data Analysis (QDA) – Qualitative Analysis deals with non-numeric data like pictures, videos or words to extract experiences of the customers.

There is no doubt that Big Data is the next Big thing in the world of marketing, but it is not complete. Graphs and Excel tables cannot provide human empathy. And Thick Data provides this missing human connection making it complete.

Helping Your Team cope up with the Fear of Data Analytics (Rank Princess)

Helping Your Team cope up with the Fear of Data Analytics

Data Analytics is one complicated word haunting software folks since quite a few years now. And the time has come to give up these fears and tackle the subject head-on.

Understanding the jargon – Data Analysis

As the name suggests, it is simply the analysis of the data at hand. It takes raw information and draws conclusive patterns. Now this data can come from various fields.

For e.g. Credit Card companies and banks evaluate their customer’s spending and withdrawal patterns to detect and prevent scams. Online marketers keep a tab on navigation trends to determine the products and services sort out the most.

Data mining is one of the methods used that goes beyond the basic analyzing of data and identifies patterns. Business Intelligence aims at concentrating and averaging the data into useful information for the business.

So basically by analyzing consumer information, companies can make informed decisions on their business. Data Analysis is also used in proving or disproving scientific theories and models.

Some quick tips to shed all apprehensions surrounding analytics of data

• Understand the basics: People need to first comprehend the meaning of Data Analytics and break it down to the smallest morsel.

• Scrutinize the data at hand: Next the records existing with the company should be examined carefully.

• Imbibe and inculcate the changes: Observe the change in trends and preferences and adjust the data accordingly.

• Do not neglect the obvious factors: Seasonal and geographical changes should always be considered.

• Discussions: Dialogues with team members can come in handy while understanding the data.

Settling the fears regarding bulk information, the focus can be shifted towards various analysis techniques

• Define the goals: Be wary of the precise information needed and focus solely on the objective.

• Optimization: This involves omitting the unwanted data and optimizing the huge information base. Decide whether you need the data to be in a structured or unstructured way and act according to it.

• Sorting: Tidy up huge amounts of data so that they are easily filtered. All the information should be effortlessly accessible.

• Algorithms and Tools: Utilize the readily available free tools and software for data sorting and comprehending. Employ data mining tools, predictive analysis methods to ease the load.

• Flexible models: Make sure that the models created to analyze information are flexible enough for future developments.

Data Analysis is a challenging field which is sort after by multinationals and start-ups alike. Once teams wrap their heads around the concept of Data Analytics, it no longer seems a scary topic. With proper education on the concept, professionals can master the art of analysis.

However, there are few hurdles holding back companies from making the best use of it. Technologies to assist in the study of vast data come expensive. There is also the inability of trainees to learn the nuances of information understanding.

Hence, large firms can incorporate Data Analysis into their domains. It further leverages their chances of coming up with new and innovative ideas to lure buyers. Data analytics can thus elevate trade to a whole new level. So shed inhibitions and embrace analytics.

Big Data SEO Sample (Rank Princess)

Do Big Data and Data Analytics Outweigh Standard Human Judgment?

So, do Big Data and Data Analytics outweigh standard human judgment?

Some of the applications of Big Data in daily life:

• Predictions made by Google while searching for things using the search engine. Google analyzes the accumulated data based on the previous queries on similar subjects.

• Intimations from debit/credit card companies about unsolicited activities based on findings from millions of transactions every day.

• Different companies take online surveys for gathering data about their clients. The resulting data is used to predict customer requirements.

• Data analytics based on the medical history of patients can help doctors in predicting patients’ responses’ to drugs and aid in finding possible cures to diseases.

Impossible for humans to process Big Data manually

Judgment making abilities of human beings are inadequate to deal with Big Data. Information of such an enormous size and complexity cannot be analyzed by our brains.

Helping people make more informed decisions

Human beings may be inefficient in analyzing Big Data but the outcomes of data analytics by computers can help them achieve meaningful conclusions.

The development of algorithms for advanced data analytics is likely to lead to social, economic and political development.

Benefiting people through Big Data

• The Management of organizations’ could become more transparent and increase workforce efficiency.

• Data analytics will offer a greater scope for performance-related experiments.

• Categorization of a population for customized results.

• Automated algorithms for effective inferences.

• Customized services will increase profitability in business.

Some drawbacks of Big Data and data analytics

Dealing with data analytics in a positive manner

Data analytics and human judgment should complement each other

Need for storing large data

Effective storage and data processing of Big Data can generate wonderful results.

Data processing can help determine the causes of failures. It can help identify defects. It can increase business by analyzing buying habits of customers. It can also help organizations detect fraudulent behavior.

In order to get important results and their subsequent utilization, there cannot be a rivalry between Big Data, data analytics, and standard human judgment.

Making do without any kind of human judgment is currently out of the question. Ruling out standard judgment can create misleading conclusions.

On the other hand, data analytics and human judgment can together reap beneficial results.