One of the most substantial big data workloads over the past fifteen years has been in the domain of telecom network analytics. Where does it stand today? What are its current challenges and opportunities? In a sense, there have been three phases of network analytics: the first was an appliance based monitoring phase; the second was an open-source expansion phase; and the third – that we are in right now – is a hybrid-data-cloud and governance phase. Let’s examine how we got here.

In our modern digital society, data is abundant, and storage is affordable. Businesses, governments and even individuals can (and do) collect every transaction, click, swipe, location, message and attribute in their datasets. With just a few clicks on my smart device, I can review data on every place I’ve been, how much I spent, every step I took, what the weather was like and who I was with. Businesses collect the same abundance of data.

Learn how small business owners can monitor the health of their business at a glance with a minimum of effort.

Sometimes I walk through the grocery store and marvel at the way customers float through the aisles, blissfully unaware of the logistical nightmare it probably took to stock the shelves. They have no idea how many people, systems, and modes of transportation it takes to make everything magically appear on their grocery shelves. But I do. As the Senior Director of Software Engineering at KlearNow, I spend my days preserving the bliss of those grocery shoppers.

The development of a digital product has been redefined to involve only 4 phases, as TCGen and Product Plan propose: However, having an easier-to-follow process is not the only improvement that you can implement: cost and time efficiency can be taken a huge step further when you incorporate analytics insights. So, with this infographic, we propose some tools that can help you analyze data sets to enrich the phases of each development process.

For modern businesses faced with increasing volumes and complexity of data, it’s no longer efficient or feasible to rely on analyzing data in BI dashboards. Traditional dashboards are great at providing business leaders with insights into what’s happened in the past, but what if they need actionable information in real time? What if they want to use their data to estimate what may happen in the future? Companies are taking notice.

Does your team know how to use data analytics to their advantage? For the vast majority of companies, the answer may be “no.” According to Accenture, only 21% of people are confident in their data literacy skills, and just 32% of companies have realized tangible, measurable value from their data. While the definition of data literacy varies depending on who you ask, at its core, the term means equipping anyone in your organization to know how to use data in a business context.