The Ledger

Why Embrace the Big Data Warehouse?

Many enterprises are struggling with their enterprise data warehouses straining to deliver value in the era of exploding data volumes and increased demand for analytics and data across the organization. They are also embracing the age of Big Data and dealing with new types of data that the enterprise data warehouse was not built to handle. All of this data is being introduced to the enterprise at unprecedented volume and speed. This Big Data is stored in systems uniquely capable of handling them, such as data lakes or cloud object storage. The business potential inherent in all of this data is demanding to be tapped, not only to improve the efficiency and quality of existing goods and services, but also to create new offerings or business models that can accelerate an organization ahead of the competition.

Read More at The Digitalist by SAP >

Challenges of Relying on Your Legacy Tools

Data management is often an enormous task for many companies, and it becomes increasingly difficult with outdated legacy systems. Finance teams require a “single source of truth” in order to be accurate and predictive. But as companies grow, many are beginning to realize that existing tools rely on legacy systems that don’t communicate with each other. This leads to data quality concerns and time-consuming tasks that don’t create any real value.

Read More at The Digitalist by SAP >

Mastering Predictive Analytics: Analyze, Predict, Act

In order to have strong predictive analytics, finance teams need to start by shifting their data conversations from data quantity to data quality. The focus on data-driven decision making leads these teams to gather all the data they possibly can without determining if it fits into their strategy.

“We must follow the mantra: analyze, predict, and act. Be careful in your analysis, ensuring that only quality data that matches your purpose is used. Use decision-driven collection, then integrate that data with information from a variety of sources. Look for easy solutions here- openness, flexibility, and an intrinsic ability to work in your systems.”

Read More at CIO Applications >

Skeptics vs. Enthusiasts of Big Data Analytics

There are a few telltale signs of skeptics and enthusiasts of analytics. Skeptics tend to be over the age of 50 and have never needed predicative analytics in their business finance processes. Today, skeptics recognize that the world has changed. It is much more volatile. But they still challenge the need to embrace deep or advanced analytics. Enthusiasts, however, are far more imaginative than that and have the analytics and computing power to be creative. Enthusiasts think forwardly with probabilistic what-if scenario analysis. Although there are differing views when it comes to analytics, there is still a need for creating a culture around it.

Read More at The International Institute for Analytics >