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Insights for Better Holiday Shopping Results

The holiday season is here again, and you do not need a crystal ball to know that the year’s biggest shopping season is here with us. According to a survey, November and December account for about half of the annual sales for many retailers. Although you might have been successful in the past holiday seasons, every holiday season is unique and often comes with its share of unique challenges. We bring fresh insights for better holiday shopping results to help you deal with this year’s challenges. With these insights, retailers are informed and inspired, and the shoppers are empowered. 

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Big Data May Help Your Holiday Plans  

As the holiday season approaches, retailers increasingly feel pressure from different quarters to deliver the best customer experience. Despite the disruption by the pandemic, reports indicate that online sales will grow significantly as the holiday season draws closer. However, the only question is, how ready are we? Have you taken advantage of technologies such as analytics to improve your business processes and seize opportunities presented by the pandemic? One of the things you can take advantage of going ahead is big data. Here are some ways that big data can help your holiday plans this year.

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What is New in Hadoop?

Ever since it became available in 2011 as an open-source program, Hadoop has made a significant impact in solving big data issues. It has also undergone significant transformations that have not only made it more robust but effective as well. Since it was founded, Hadoop has gone through major changes in versions that have made it stand tall in the big data arena. The good thing about Hadoop is that it has an active community that releases updates that keep the platform new. The latest update on Hadoop is Apache Hadoop 3.x rolled out in 2017. This new version comes with bug fixes, features, and enhancements over Hadoop 2.x. Here are some of the new features that will boost Hadoop in version 3.x that you need to know.

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Don't Overlook the Small Data

Big data continues to be a major talking point for many organizations. It is now a leading concept that continues to capture the imaginations of brand marketers and business executives looking to capitalize on it to change the landscape to their advantage. Indeed, the ability of a business to capture vast sets of data, collect vast data ranges in real-time, and process data into valuable insights can change the tide and make a business an absolute force. However, running big data is not only complicated but expensive as well.

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Are You Managing these Big Data Issues?

Data has become one of the most crucial resources in organizations today. Unlike in the past, no business can succeed without data which is vital in decision-making. With massive amounts of data being generated every second from business transactions, customer interactions, and sales figures emanating from various sales platforms, data has become the fuel that drives businesses. All this data is referred to as big data. Data from multiple sources coming to an organization needs to be gathered and analyzed to enhance decision-making. However, this is easier said than done. There are various challenges to big data that are encountered during this process. Here are some of the issues that you should manage in your big data initiative.

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What Does Internet of Things Have to do with Big Data

In the world today, we are facing three technologies that have the potential to take how we work or do things to a new level. These technologies are big data, the internet of things (IoT), and artificial intelligence (AI). These three technologies work together in many perspectives and can take different industries and businesses to the next level. Although they are closely related, they are so distinct in a variety of ways. The main question, however, is what will happen if two of these three works together? Here, we highlight the relationship between the internet of things and big data, two of the three technologies that are currently a buzzword in every tech discussion.

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Big Data Challenges Are Not Going Away in 2021

2020 was a year with so many domestic and global challenges. But the big data industry seems to have grown, even more, gaining more force moving into 2021. The growth in this area was occasioned by the rise in online activities due to the pandemic. As we start a new year, big data is expected to grow even more to heights never experienced before. Despite the growth, many challenges should be expected in 2021. Here are some of the 2020 big data challenges that are not likely to go away in 2021:

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Can Big Data Help Avert Catastrophes?

Disasters are becoming too complicated and common in the world. Increasingly, rescue and humanitarian organizations face many challenges as they try to avert catastrophes and reduce deaths resulting from them. In 2017 alone, it was reported that more than ten thousand people were killed, and more than 90 million were affected by natural disasters worldwide. These disasters range from hurricanes and landslides to earthquakes and floods. The years that followed turned out to be equally calamitous, with things such as locust invasions, wildfires, and floods causing havoc across the planet.

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Who Should Manage Your Hadoop Environment?

Hadoop is the leading open source technology for the management of data. In any discussion about big data and its distributions, you will never fail to come across Hadoop in the middle of the talks. As outlined in a technical paper by Google in 2006, it was designed as a distributed processing framework back in 2006. It was first adopted by Yahoo in the same year, followed by other tech giants such as Facebook, Twitter, and LinkedIn.  During this time, Hadoop evolved significantly into one of the most complex big data infrastructure known today.

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What is Important in Data Transformation?

Data has become one of the critical components of any business in the modern era. It is for this reason that you keep hearing some conversations around big data and big data analytics. With this, data transformation has also gained fame. It is the process where data is analyzed, reviewed and converted by data scientists from a given format to another. This process is essential for organizations, especially at a time when data integration is required for an effective running of operations and security. It might involve the conversion of large amounts of data and data types, elimination of duplicate data, enriching data and aggregating it. Here is how data is transformed:

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