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Big Data

Challenges with Big Data Visualization

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This is a big data era, where every moment of life is calculated and is store in some or other manner. Scientists, who continuously work for the future predictions, advanced computing and other growing technologies continuously require a quick look over the data of past several years, and so these studies and requirements are giving a blast of data which is crucial to maintain immortally. The major challenge is to store and maintain this giant data with a flexibility to visualize the data in static or dynamic form. In previous decades people did had data and data management tools too, but now the volume of data has grown exponentially. Traditional data management tools are not really effective and even efficient to combat the current scenario.

Let’s first define the attributes of big data which evolves major challenges:

Volume:

Big data, by name itself it justifies the definition that means a huge sized data that is generated at a period of single day. Now there is nothing like important data and casual one, each data generated in per day time is been stored and processed and this is one of the major challenges faced by big data management.

Velocity:

There are certain channels for data transmission and the velocity and frequency with which s being transferred through the channels generates a heavy congestion in the channels making it challenging to maintain.

Variety:

During past era, there was certainty for the formats of data to be stored, as data were well defined following the data schema. With the technological expansion it also gave an expanded world for data with a huge variety of data to be generated and hence also increased the requirement of data maintenance, processing and transmission.

Value:

The value of data keeps varying with every data generation. It is the biggest challenge for the big data management to evaluate every single data before processing and transmitting it. This is crucial so as to segregate the data as per its value which makes the data mining process easier and faster too.

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Big Data

Fraud detection with big data analysis

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World is moving to the digitized platforms and this digital approach is also giving a strong way to the intruders to enter any digital network and violate the data stored in that specific network. In present world, every single digital network is at a high risk of malicious activities. To maintain the privacy of the network we require robust solutions that safeguard our networks by providing alerts timely. Big data analysis is one of the most potential solutions that help various businesses in safeguarding their networks. There are a wide range of data protection solutions offered by the big data which is far beyond the limit of computer monitoring and other traditional network securing solutions.

Suspicious cases detected with the help of big data are:

Unusual data:

Data types are now limitless and the combination that it figures out is more complicated making the output unusual and unexpected. To understand the countless combinational patterns and make it viable for various uses we require a potential platform that frames the possible combinations, detects all unusual data and make it easier for the user. Unusual data are distinguished into three situations, i.e. unusual combinations, unusual data with respect to the group, and unusual values. Any combination or value input that looks unusual to the pre-determined data sets can be easily detected using big data analysis.

Unexplained relationships:

Combinations of input data play a crucial role when you are working with a sensitive data to limit the access to limited authorities. For example, online transactions are based on several combinations and relationships of input data. Most of the transactions are carried by making a wide set of data combinations and a perfect match only allows the transactions. One or two data from the pre-determined set may match from the countless combination, but matching entire set is impossible. Big data helps the experts to understand the unexplained relations distinguishing the data sets.

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Big Data

Big data revolutionizing the marketing industry

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Big data is a hot topic in the world of marketing. When you talk about marketing, the sector reflects a lot of challenges and fewer opportunities to reach out correct audience for the maximum outcome. With big data, anyhow the challenges are not going to reduce but you will get a plethora of opportunities in advertising your brand to the right audience, at the right time at right place. The major challenge of marketing industry is the competition which it faces at every step. Big data offers several creative ideas that strategies your marketing tactics and help you coming out with more customized and innovative ideas making you stand out among the rest and cutting down the competition.

What can big data change in marketing?

Forecasting and planning:

Forecasting is the foundation for all the marketers. Till the date, most of the marketers were working on a hit and trial method when it came to forecasting. Now, with the help of big data forecasting has got more accuracy and easier. Now, forecasters can grab details of several years; check the trends and collect a wide range of information used for making their report. This detailed analysis brings aptness to their work.

In forecasting, the marketers don’t need to spend a lot of time in research, instead they can attain the entire ready to use information, such as current market trends, consumer’s demand, shortage of commodities and many more.

More audience targeting:

With online marketing a huge pool of audience has been opened in front of marketers. From this huge pool now you can select your targeted audience easily by keeping an eye on their previous shopping, their browsing history, and other online activities. This is possible with the help of big data which help your website to place cookies in your viewers system and then analyze their online activities, track it, store it and use it for your further marketing activities.

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Big Data

In what ways big data abetting the digital transformation?

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One of the key factor for digital transformation is the big data. An organisation has huge data which is generated, collected frequently so these organisations are in search to adapt new technologies where the scope for digital transformation is accelerated. To digitise any organisation, it is imperative to implement useful data with specific methodology.

Big data helps enabling this digital transformation by following:

Digital marketing:  helps in analysis of customer’s behaviour and their preferences, hence market their products using big data available there by ensuring customer encouragement. Audience are being targeted on basis of data of revenues and sales of specific product. The combination of big data and marketing helps the organisation to reach various spots of industry.

Big data and 5G: digital transformation is accelerated only when there is good, fast and reliable communication networks which becomes paramount.

Recognising the flaws with big data: to yield maximum advantages, integrating big data with systems will aid in searching the loopholes where there is drawbacks in operations. Like in demand and supply chains, the big data analytics will assist to search drawbacks in the operations or in any product’s statistics which helps the brand to improvise the products and come up with a strategy to rectify the flaw in beginning stages.

Cyber security: when an organisation digitally transform they become open to malwares and cyber-attacks, therefore it becomes a threat to security systems of an organisation. So with help of data analytics and big data it is easier to find those areas where the probability is higher for cyber-attacks. Which helps to upgrade the security structure and alleviate the cyber-attack.

While big data governs the digital transformation, it could be hazardous for an organisation infrastructure too. Operations are interrupted when data is corrupted. So it is necessary for an organisation to be careful while using data for the digital transformation.

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