Getting Big Data to Actually Work
Most marketers I talk with today say they are drowning in data. But in reality data they really want sits in disparate systems throughout the organization. Or if their company has invested big money in a traditional data warehouse, the results have fallen short of expectations. This is because traditional data warehouses were never designed to handle the volume, variety and velocity of today’s data-centric applications. So, while most marketers and most companies “talk” about big data they just go on with “business as usual” taking little or no action.
This is not just my opinion. Recently, my UK colleague, Richard Petley, director of PwC Risk and Assurance, conducted a survey of 1,800 senior business leaders in North America and Europe. And only a small percentage reported effective data management practices. 43 percent of companies surveyed “obtain little tangible benefit from their information,” while 23 percent “derive no benefit whatsoever,” according to the study. That means three quarters of organizations surveyed lack the skills and technology to use their data to gain an edge on competitors.
The problem is not access to data. It’s the management of it. What companies really need is the ability to manage large amounts of data in a safe, agile and adaptable fashion. And that means they need a more modern data warehouse.
The overall purpose of a data warehouse is to integrate corporate data from various internal and external sources. Implementing a data warehouse is traditionally a long, costly and risky process. When the solution is ready, it’s often slow, outdated and hard to update as business changes. A modern data warehouse is different – employing new technologies, products, and approaches. Approaches that allow for both speed and agility.
With a modern data warehouse, you only have to query one source to get the data you need. When you add automation to the mix, you can load, clean, integrate, and format the data in record time.
POSSIBLE is a creative agency that brings results-driven digital solutions to some of the world’s most dynamic brands. Every two weeks, analysts faced the herculean task of reporting campaign results based on 10 different data sources, applying 20 different measures on 70+ products delivered by 100+ media partners. They would spend on average 35 hours just processing data before they could begin analysis.
When I spoke to the POSSIBLE team they reported this free demo introduced them to a data warehouse automation tool from TimeXtender. After a surprisingly fast implementation period, the “data munging” performed by POSSIBLE’s analysts has now been reduced 68%. “This has really turned out to be a big win for us. The fact that we can now get actionable data to analysts so much faster allows us to spend more time providing valuable insights to clients,” says Harmony Crawford, Associate Director of Marketing Sciences.
As my colleague Richard Petley likes to say, “Data is the lifeblood of the digital economy.” It can provide insight, inform decisions and deepen relationships, and drive competitive advantage, but only if it’s managed in an agile and adaptable way.
So the next time you find yourself complaining about the problem with big data, stop talking and start researching the modern data warehouse and data warehouse automation.
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