The customer journey is incredibly complex today - thanks to rapid technological advancement. Our digitally-focused culture allows businesses to connect with their customers through more channels than ever before. But, it also makes it even more challenging to optimize and determine which methods are driving in the best results. In order to figure out which specific marketing … [Read more...] about Your Mobile Marketing Data Is Dirty – But These Mobile App Attribution Techniques Can Help
Big Data
Learn everything you need to know about big data. Find out how companies are using this revolutionary technology and what it means for your business strategy.
Psychology of the Connected World
It's true that the surrounding technologies are changing not our lives but also our behavior and attitudes. They or, rather, their creators learn not only to help us, but also to manipulate us in new ways. Our over-trust to technologies might be underneath the new notion of post-truth where nothing is ever probable. The recently emerged era of the connected world has produced … [Read more...] about Psychology of the Connected World
9 Formidable Big Data Analytics Tools for 2019
Typically big data is reckoned by its size, but experts also give credit to information technologies that are assisting analysts in analyzing huge clusters of unstructured data to make sense of data trends, patterns, and anomalies. Big Data is a crucial asset for Business Intelligence (BI) for industries ranging from manufacturing to banking, professional services to … [Read more...] about 9 Formidable Big Data Analytics Tools for 2019
15 Books by Leading Software Architects
As you may already know, Apiumhub team is software architecture-oriented and reads books for software architects on a weekly basis. This year Apiumhub organizes Global Software Architecture Summit 10th of october, which will take place in Barcelona. Leading software architects from all around the world will come to discuss work habits, best practices and definition of software … [Read more...] about 15 Books by Leading Software Architects
Data Engineering From A Data Scientist’s Perspective
We've had technical people focused on the ingestion and management of data for decades. But, only recently has data engineering become a critical, widespread role. Why is that? This post will outline a somewhat contrarian view as to why data engineering has become a critical function and how we might expect the role to evolve over time. IIA expert Jesse Anderson recently wrote … [Read more...] about Data Engineering From A Data Scientist’s Perspective
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What is big data?
Big data is a term that refers to the massive amount of digital data created and shared every day. Big data can transform how we live, work, and communicate. It can be used to improve everything from public health and urban planning to business and marketing.
Big data is also changing the way we think about privacy and security. The volume, velocity, and variety of big data present challenges and opportunities for organizations and individuals. Regardless, big data is here to stay, and its impact will only continue to grow in the years to come.
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What is big data analytics?
Big data analytics is the process of turning large, complex data sets into actionable insights. Businesses use various analytical tools and techniques, including machine learning and statistical analysis, to do this.
Big data analytics can be used to improve decision-making in areas like marketing, operations, and customer service. It can also be used to identify new business opportunities and optimize existing processes. With the help of big data analysis, businesses can gain a competitive edge by using their data better.
Want to learn more about big data? Datafloq has courses available. Contact us to get started.
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When was big data introduced?
The term big data was coined in the 1990s, with some giving credit to John Mashey for popularizing the term. However, the concept of big data has been around for much longer.
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Where does big data come from?
In the early days of computing, scientists and businesses began to realize that the amount of data being generated was increasing exponentially. As a result, they began to develop new methods for storing and processing data.
Over time, these methods have become increasingly sophisticated and have played a key role in enabling businesses to make sense of vast amounts of information. Today, big data is used in various industries, from retail to healthcare, and its importance is only likely to grow in the years to come.
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What are examples of big data?
One of the most common examples of big data is social media data. With over 2 billion active users, Facebook generates a huge amount of data every day. This includes information on user interactions, posts, and even location data. Analyzing this data can help companies better understand their customers and target their marketing efforts.
Another example of big data is GPS signals. These signals are constantly being generated by devices like cell phones and fitness trackers. When combined with other data sets, GPS signals can be used to provide insights into everything from traffic patterns to human behavior. Finally, weather patterns are another type of big data set. By tracking these patterns over time, scientists can better understand the impact of climate change and develop strategies for mitigating its effects.
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How do companies use big data?
Companies use big data in marketing, product development, and customer service. By analyzing large data sets, businesses can identify patterns and trends that would be otherwise difficult to spot. For example, a company might use big data to track customer behavior patterns to improve its marketing efforts.
Alternatively, a company might use big data to improve its products by identifying areas where customers are most likely to experience problems. For instance, big data can be used to improve customer service by finding pain points in the customer journey. Ultimately, big data provides companies with a valuable tool for gaining insights into their business operations.
