Nowadays, absolutely everything is based on data. It doesn’t really matter if you sell shoes, run a marketing agency or produce bicycle tires. Data is essential for you. You use it all the time. Data helps you in almost everything you do. From searching on Google, through hiring new workers up to creating financial reports. It really is all about data. Check our examples of data science projects! Data Science applications can offer various benefits. Before diving into the development process, it is essential to understand the business goals and identify areas where data can be utilized to ach ..read more

According to a report by BARC Research, businesses that leverage big data see a profit of 8% to 10% and a significant decrease in overall operational costs. [1] However, between 60% and 73% of enterprise data is never used for analytics, which means that up to three-quarters of all collected data goes unused. [2] This begs the question, how can businesses effectively analyze and derive actionable insights from collected data? That’s where big data knowledge management comes into play. This guide will delve into the intricacies of big data knowledge management, evaluating everything from what i ..read more

The ability to collect, analyze and use data to make strategic business decisions has always been the key to success for most companies. According to a recent report by McKinsey Global Institute, data-driven businesses are 23 times more likely to attract new customers, six times more likely to retain customers, and 19 times more likely to become profitable and attain long-term success. [1] That said, the ability to effectively manage data has never been so critical. This is where a DataOps platform comes into play, providing a streamlined and efficient approach to managing data, enabling busin ..read more

Many companies generate massive amounts of structured, unstructured, and semi-structured data. But they lack the time and resources to build on-premise data systems, develop an analytics toolset stack, and hire an in-house team of data scientists. As a result, the data often goes unused. This is where big data as a service (BDaaS) comes in handy. Organizations can instead hire the data management systems and toolsets of an outside provider. In doing so, they can save on organizational resources and still process, manage, and evaluate their large data sets to derive insights and gain a competit ..read more

43% of decision-makers in IT dread that the rising levels of data influx might overwhelm their data infrastructures in the future [1]. The necessity for businesses to make data-driven decisions, coupled with the ever-increasing disparity of data sources, has necessitated the need for robust data infrastructures that can extract, transform, and load data rapidly and efficiently. Also, because most businesses generate data in a transactional database, which is not ideal for running analytics, the need for a data transfer system that can move data from the source to the storage and process it in ..read more

The big data market value stood at USD 162.6 billion in 2022 and is projected to reach USD 273.4 billion by 2026 at a compound annual growth rate of 11%. [1] One of the many reasons behind these huge numbers is that big data solutions have revolutionized many industries, and the telecommunications industry is no exception. Read on to find out how the telecom industry can exploit the power of big data. Telecom companies generate huge volumes of data from mobile phone usage, call detail records, server logs, network equipment, social networks, and billing. In other words, they are sitting on a g ..read more

Not so long ago, data warehousing was the buzzword among major organizations looking for an efficient means of data storage. A few years down the line and big data came into the picture, with some big industry players speculating that it could end up replacing legacy data warehouses. However, when you look closely at big data and data warehouse technologies, you realize they share many similarities. For starters, both of them can hold huge amounts of data and can be used for reporting. This begs the question, how different are they, and could big data replace data warehouses in the future? Fin ..read more

The Economist published a statement that reads, “The world’s most valuable resource is now data.” [1] Historically been treated as just a piece of a technology project and not a corporate asset. Many business executives assume that conventional application and database planning endeavors are adequate to resolve current data issues. But business data reserves have grown in volume and subject area variety, necessitating the need for a data strategy to inform how a company’s information assets can be managed. Read on as we take you through how to develop and implement a data strategy framework. T ..read more

The phrase “big data” can be traced back to Silicon Valley lunch-table conversations and pitch meetings in the 1990s[1]. It’s a relative term depending on who is discussing it, but one point remains constant: The 21st century has witnessed the greatest explosion of data in history. And that’s why big data platforms and big data consulting became indispensable. Up until 2003, the total volume of data recorded was 5 exabytes[2]. In the year 2011 alone, the amount of data recorded was 1.8 zettabytes, which is about 1000x more. Moving forward, it is projected that mankind will produce 463 exabytes ..read more

Since the early 2000s, the volume of data generated and the rate at which it is generated have increased tremendously. In 2018, more than 25 quintillion bytes of data were generated every day[1]. This trend is primarily driven by the ever-reducing cost of storing data automation in smaller devices. At this rate, even data warehouses will start getting overwhelmed with an influx of data[2]. Traditional database management systems were designed to store structured data. But with the advent of big data, such systems are becoming obsolete, thus necessitating businesses to come up with more effecti ..read more