Big Data

With organizations that rely heavily on their supply chain, designing actionable performance level metrics, those that actually matter is even more important than the top level financial drivers.

Evaluating BI vendors can be a confusing and complex process. However, knowing the right questions to ask can greatly reduce the risk of selecting the wrong solution provider. The right BI solution must provide business decision makers with the information needed to obtain operational and strategic business objectives.

Why risk building you own business analytics solution from scratch? How long will it take you, how much will it cost to support and how confident will you be in the data?

Okay, so you’re committed to rolling out Business Intelligence across your supply chain, you have tons of data, so how do you turn that data in to actionable information?

We believe that the adoption of new concepts for big data is a step change for supply chain teams. It is not about force-fitting new forms of data into applications based on relational databases. It cannot be treated as an evolution.

Association's leader says he is excited to be part of the supply chain and material handling buzz on the social networking site.

Powerful new tools could give us a better picture of what's going on across our supply chains.

The McKinsey Global Institute estimates that data volume is growing 40% per year, and will grow 44x between 2009 and 2020. But while it’s often the most visible parameter, volume of data is not the only characteristic that matters.

Big Data has much to offer the world of logistics. Sophisticated data analytics can consolidate this traditionally fragmented sector, and these new capabilities put logistics providers in pole position as “search engines in the physical world”.

Almost seven out of 10 business leaders believe supplier risk analysis will become more complex as they expand into new global markets. That’s according to research by the Economist Intelligence Unit’s report Strategies for managing customer and supplier risks, sponsored by Dun & Bradstreet.

Implementing a Big Data project might make sense for your organization. But before you start investing in the time and resources required, make sure the effort will ultimately enable you to differentiate between the beneficial “signals” and the distracting "noise.”

In today’s dynamic global marketplace, increasing logistics flexibility is critical as shippers look for greater collaboration with their third-party providers on the way to seamless integration of supply chain activities.

The report presents two big data application examples and shows how each would be implemented using 1) data warehouse technology and 2) Hadoop. It then calculates the five-year TCOD for each solution.

Learn how to gain business insight using MapReduce and Apache Hadoop with SQL-based analytics.

With customer data spread across multiple systems and databases, Syncron’s Global Customer Master (GCM) is the centralized repository that consolidates all the customer reference data, along with the cross-references to source systems, into a master reference store.