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Exploring the depths of data – what is a data lake?

When we talk about the vast amounts of data being generated each year, it makes sense to ask the question, “where is it stored?”.

In simple terms, it is stored in the illusive ‘cloud’. Data kept in cloud storage is held on remote servers which are accessed via the internet.

There are however, a couple of ways of storing big data in the cloud, depending on how much information you have, the types of data stored, where it is being pulled from and who has access to it.

The two standard storage concepts are a ‘data lake’ and a ‘data warehouse’.

Comparing a data lake and a data warehouse

TechTarget describes a data lake as “a storage repository that holds a vast amount of raw data in its native format until it is needed”. While a data warehouse is similar, in that it stores large volumes of data, it just takes data from operational systems, whereas a data lake also interacts with other data sources. This could be a data intake tool like Ventiv Digital.

The other main difference is how data is stored. A data warehouse structures information into files and folders, as you would expect in your company’s network folders (e.g. in SharePoint or OneDrive). However, as a data lake accommodates data, often unstructured, from various sources, it uses a flat system. Each piece of data is given a unique identifier and a series of metadata tags. This enables the information to be interrogated using a combination of search criteria.

How can a data lake stop you drowning in data?

It is estimated that the world’s data storage will reach 175 Zettabytes by 2025 – that’s a 500% increase on 2018 (IDC and Seagate). That is a lot of data.

Large volumes of structured and unstructured ‘raw’ data is usually referred to as ‘big data’. The main challenge of having big data sets is integrating systems to enable access to all information at once, and then turning it into a manageable, useable form. A data lake turns big data into a searchable format for the purpose of business reporting and analysis.

Big data becomes valuable to an organization when it can be interrogated and turned into usable insight through analysis and reporting that in turn, feeds into your business strategy.

The value of data lakes in risk management

Risk managers often have access to copious amounts of data from across a business. If this can all be stored in one data lake, and be tagged and searchable, an advanced analytics application can be employed to create actionable insight.

Software, such as Ventiv’s Advanced Analytics, is designed to do just that. Drawing on internal business and external industry data sources, risk managers can interrogate it to answer the big questions that matter to their organization. With real-time analytics, data discovery, and prescriptive and predictive analytics in a risk manager’s toolkit, a business can easily develop reports that identify risks, opportunities and potential income generating streams.

At Ventiv, we have our own Analytics Cloud. Here we can store data from your applications e.g. Ventiv IRM, where you can run queries without having to download lots of data to your system. You can access information stored from anywhere with an internet connection.

A fully integrated data lake is accessible 24/7, fully auditable and GDPR compliant, and exploring the possibilities it can bring to your business should form part of your digital strategy.

 

David Thomas is the Sales Director at Ventiv Technology. If you would like any further information on this topic please contact him at DAVID.THOMAS@VENTIVTECH.COM
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Sep 27, 2019

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