When running a business, it's easy to get overwhelmed with the sheer amount of data that's put in front of you. These days, the problem no longer lies with how or where to acquire more data; instead, it's figuring out how to convert the raw data you already have into actionable insights. After all, data is useless without any meaning. Therefore, it's about time you put it to … [Read more...] about Converting Data into Insights: 4 Steps To Improve Your Business Efficiency
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.
Cloud Computing: Transforming IT Infrastructure into a Utility
Cloud computing turns IT infrastructure into a utility by allowing you to 'plug into' infrastructure over the internet and use computing resources without having to install and maintain them locally. What is Cloud Computing? On-demand services offered over the internet are referred to as cloud computing. In simple words, cloud computing is the distribution of computing services … [Read more...] about Cloud Computing: Transforming IT Infrastructure into a Utility
How to Use RLS Roles and Filter Expressions for Dynamic User-Based Visibility in Power BI?
Data security, wherein users or groups of users are prevented from viewing a portion of a dataset, is often a top requirement in Power BI deployments. This article is a part of a larger chapter around dynamic user-based filter context techniques from the book, Microsoft Power BI Cookbook, Second Edition by Greg Deckler and Brett Powell. This cookbook helps you build … [Read more...] about How to Use RLS Roles and Filter Expressions for Dynamic User-Based Visibility in Power BI?
Using Data Matching to Resolve Identity Resolution Challenges
Consumers interact with a brand through hundreds of touchpoints across devices, platforms, and channels. During the buyer's journey, consumers use 3-4 internet-connected devices. And by 2021, the number is expected to increase to 13 devices. This exponential increase in device usage indicates a sudden surge in data as well. This data influx is demanding organizations to have … [Read more...] about Using Data Matching to Resolve Identity Resolution Challenges
7 Ways the IoT Makes Farming More Precise
Thanks to contextual and real-time data, we know more about our environment than ever, and that's making some pretty big waves in the farming and agriculture industry. IoT in agriculture delivers new insights that improve efficiency, profitability and yield, which grows more important every day due to climate change. Crop yields will determine whether or not we face food … [Read more...] about 7 Ways the IoT Makes Farming More Precise
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.
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.
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.
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.
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.
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.