In a series of articles collected in the problem statement "Preparing for Big Data" we have outlined the concept of a data lake, a vision for a much wider, less organized form or storing and managing data for business intelligence purposes.
Preparing to take advantage of the business value that big data can provide is going to be a multi-year process that takes place in several stages. Most of the new sources of data arriving under the banner of big data are fundamentally different than the type of data stored in most data warehouses.
CITOs are now facing an infrastructure build out to support big data. How can they avoid the mistakes of the past and end up with an environment that is at the same time enterprise quality but also agile?
Agile Big Data is based on the lessons of business intelligence. Traditional Business intelligence, aka Enterprise BI, is powerful but hard to configure. Agile BI is a new class of BI that is easier for users to control and use on their own.
This article is a CITO Research Overview of Attivio, and will attempt to answer the following questions:
The idea that the amount of data is rapidly growing has come to be called “Big Data” in journalistic and analyst circles. “Big Data” refers to the fact that machines are producing data in volumes never before seen in recorded history. There are significant opportunities to analyze and exploit that data to find business insights.
Everybody knows about IRS audits. Much less well understood are Oracle audits where the software behemoth comes into a company and – much as the IRS wields the proverbial fine-toothed comb to hunt for irregularities – Oracle uses its version of a fine-toothed comb to sift through a company’s software library and its licenses. Every piece of software is inspected, and so are the appropriate Oracle licenses and contracts.
How is your organization going to harness the power of mobile devices? In many ways, the answer to this question is a proxy for your approach to technology in general.