Analytics

Analytics (45)

Creating Systems for Real-Time Processing and Analysis of Streaming Data

Data streaming is a continuous flow of data generated by various sources, like social media, sensor networks, and financial transactions. With the competitive nature of the business landscape, the ability to process and analyze this data in real-time is becoming increasingly important for businesses, as it allows them to make timely and informed decisions. However, real-time processing and analysis of streaming data are not without their challenges.

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Using Machine Learning Algorithms to Make Predictions and Automate Decisions

Machine learning algorithms are a type of artificial intelligence that can be used to make predictions and automate decisions. These algorithms are trained on data and can learn to recognize patterns and make decisions based on that data. This makes them an effective tool for businesses looking to improve efficiency and make better, more informed decisions.

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Cleaning and Preprocessing Data to Prepare it for Analysis

Data preparation is an essential step in the data analysis process. It involves cleaning and organizing data to make it ready for analysis and visualization. In this article, we will discuss the benefits of data preparation in the cloud, the steps involved in the data preparation process, and the tools and technologies available to help with data preparation.

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Online Black Friday Spend Swells to a Record Breaking $9 bln

Despite high inflation rates – online Black Friday sales in the United States set a new high. On Friday, Americans flocked to their computers, tablets, and cellphones and spent a whopping $9 billion in just 24 hours. An increase of 2.3% from last years’ sales - Adobe Analytics cited the increase was partially due to consumers waiting until November 25th to purchase items versus taking advantage of the Black Friday deals that began earlier this year.

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Disaster Relief and Big Data

Big data analysis is proving to be highly beneficial to businesses. The patterns are beneficial to business practice and can improve the efficiency and effectiveness of managing disasters and emergencies in organizations. Thanks to the availability of mobile devices such as smartphones, disasters can be measured in real-time and information relayed to people for rapid, efficient and accurate response. The use of big data to predict and help with disaster relief comes after centuries of struggle. Therefore, agencies can respond to disasters quickly and effectively by adopting and analyzing big data. Here are some ways that big data is helping in disaster relief.

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Data Analytics May Change the World

Data analytics is proving to be an excellent tool, not only for business but for the planet as well, going by how it is helping fight climate change and helping society in general. While many have associated it with its uses in the business environment, it is proving to be the change that the world needs at a time when the fight against climate change is taking shape. In addition to helping in climate change initiatives, big data analytics will help improve other areas such as entertainment and health and research, among other fields. Here are some of the biggest areas that data has on the world.

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Data Analytics for Your Business

Data analytics has proven to be a critical part of modern businesses. It can help improve decision-making outcomes for almost any type of decision, which can be micro, macro, strategic, operational, cyclical or tactical decisions that will help propel a company to the best possible heights. Data analytics can help unearth new solutions to problems and opportunities that business leaders would not have found if they continued using conventional methods. Progressive organizations employ data for various things and therefore must rely on data from within and outside the organization to make smart and informed decisions.

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Stay Away from these Mistakes with Your Data

Big data and analytics have become a success story for some organizations. However, most of them have never realized the full potential of big data because the real power of this technology has been restricted to small parts of their operations and businesses. Therefore, while others have immensely benefitted from big data, some are still struggling to see how it will help them. According to Gartner, only 20% of analytics insight will deliver the business outcomes this year. This low percentage of delivery is due to various mistakes. Due to this challenge, this article lists some mistakes you should avoid in your big data initiatives.

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These Data Analysis Projects are Gaining Attention  

Data analytics projects can be challenging to many organizations, especially those entering the murky waters of data analysis for the first time. While you may think data projects need to be complex or showy, that is not always the case. Rather, the most important thing you should do is demonstrate your skills using data sets that interest you. The good news is that any organization, regardless of the time they have spent, is that data is everywhere, and you need to know where and how to find it and what to do with it.

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Watch Out for These Common Analytics Mistakes

Technology is advancing at a fast rate. The same can be said about the emergence of new devices and their data. With vast data emerging from different sources, new approaches are adopted to process data and gather insights. As such, data analysis has gained fame. While big data analytics is a good thing for your business, mistakes can be made in the data processing. As you seek to implement this technology in your organization, watch out for these common analytics mistakes in your operations.

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