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Big Data vs. Good Data: Why You Need to Know the Difference

Hungry for insight, organizations of all sizes have invested in data science. They have purchased an array of functional and analytic tools—CRM, BI, HR, POS, and ERP. They have tasked teams with gathering data from these applications and filling in the gaps between them.

Volume over value
Yet what begins as a ‘data science’ project can quickly devolve into a scavenging operation. Zealous organizations pour resources into identifying and tracking and storing every viable metric, including those only loosely connected with business success. They end up drowning in more data than they could ever analyze.

Insight is inherently beneficial. Data is not. Organizations can swamp themselves with data—say, every tweet their prospects have ever posted, or the past ten years of temperatures in the prospect’s city—without having any impact on decision-making.

Systems of reference
So how can businesses track the right metrics? One answer lies in a single system of reference like an ERP solution.

But most ERP systems offer only limited BI. They will store the customer’s accumulated data, but the customer’s own data teams must still try to wring meaning out of it. Integrations are often unwieldy, requiring constant repairs.

Therefore, any system of reference must combine unified design with robust BI functionality. Integrations should be minimal and reliable where necessary. The customer should be able to see their organization’s financial health in real time.

The answer
Xledger delivers precisely such a solution. With 10,000+ customers on one software instance, Xledger pairs market-leading automation with unparalleled BI power. Xledger customers have a wide range of tools to analyze their data, from configurable reports and dashboards to multi-dimensional inquiries. Beyond mere software, Xledger consultants work with customers to impart best practices and define crucial KPIs.

Big data cannot drive success. Only insight can do that.