Looking Inside A Big Data Toolbox

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Big-Data-Toolbox

Big Data Toolbox

Big Data Toolbox- Much like term super, the big in big data comes with a certain amount of hype. Just as we now have supercars, supermodels, superspreaders and super-sized meals, we now have big business, big data and of course Big Macs.

Regardless of the hype cycle, big data has firmly entered our tech-business vocabulary. We now use it as a kind of blanket term when we talk about the massive web-scale information streams being passed over the cloud, inside the Internet of Things (IoT) and throughout the new realms of Artificial Intelligence (AI).

Broadly meant to refer to an amount of data that is too large to fit comfortably or productively into anything that resembles a ‘traditional’ relational database management system, big data is still just data… but it includes core operational enterprise data plus all the pieces of information that an organization knows it has, but is perhaps yet to act upon.

No-code wrench and spanner in the big data toolbox

To wrangle our way through the mire of big data, an increasing number of software companies are getting into the big data tools business. So what size and shape are these tools and what do they do?

No-code data access platform company software Okera reminds us that large organizations have a variety of data access control use cases, which means they require flexible Attribute-Based Access Control (ABAC) policies. An ABAC policy can combine multiple attributes, including user, tool, type of data and location, to enable self-service analytics while ensuring secure, compliant access to data.

When enterprises allow access to the big data estate, not every employee should be able to get access to all the information that exists, for obvious reasons related to privacy and security. Okera has automated tools for this kind of function. This process is known as dynamic data masking (i.e. transforming data to a structurally similar shape but with inauthentic values for testing purposes) and data tokenization (i.e. transforming data values into a placeholder token that is random and unidentifiable) and both may be brought into play concurrently.

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Article Credit: Forbes