Wally McDermid, VP Strategic Alliances And Business Development at Scality, explores how organisations can avoid data swamps, and how they can leverage object storage to effectively manage a data lake.
For organisations struggling to manage and draw value from massive and growing volumes of unstructured data, data lakes are an appealing and practical option. Yet without careful organisation, those lakes can quickly turn into sprawling data swamps, making it arduous for IT teams to locate the data they need. Not only is this time-consuming and costly, it can expose the organisation to new security threats. In this article, we will explore how to leverage object storage to keep data lakes easily accessible, well-organised, and secure.
Defining data lakes and data swamps
To put it simply, a data lake is a centralised repository that houses data in multiple formats and from various sources. Gartner describes it as, “a concept consisting of a collection of storage instances of various data assets. These assets are stored in a near-exact — or even exact — copy of the source format and are in addition to the originating data sources.”
A data swamp, on the other hand, is an unorganised pile of data without any categorisation or taxonomy. Navigating through a data swamp resembles wading through a bog, hoping to stumble across the required information. This strategy is clearly neither efficient nor secure. It’s simply not possible to keep data safe if you do not know what you have or where it is.
Maintaining cleanliness and organisation in a data lake is key to avoiding it becoming a data swamp — and that’s where object storage can help.
The role of object storage in avoiding a data swamp
Without proper structure and metadata, locating specific data becomes a daunting task, similar to searching for something in a literal swamp. Object storage effectively tackles this challenge by organising information into flexibly sized containers known as objects. Each object contains both the data and associated metadata, and is identified by a unique global identifier rather than a file name and path used in file storage. These systems can be enhanced with custom attributes to handle additional file-related information, which makes finding data that much easier.
Data lakes can quickly expand to petabytes and beyond, requiring a solution capable of handling immense capacity. Object storage is an ideal solution in this scenario, enabling seamless and horizontal scaling as data continues to proliferate from diverse sources.
A competitive advantage
With a clean and effective data lake, IT teams not only ensure they can find and access data when they need it, but they can gain valuable insights from their data. Being able to fully reap the business insights within data lakes depends on both analytics tools and the storage repository.
The storage system must be able to process data from various sources and to scale in terms of both performance and capacity so data is accessible to applications, tools, and users. The right solution will deliver the performance, scalability, flexibility, and lower cost that organisations require to keep their data lake clean and gain a wealth of other benefits from it.
The analogy of a swamp highlights the challenges associated with locating, utilising, and securing data without a strategic approach. Object storage emerges as an ideal solution to ensure data lakes are organised and accessible. By embracing object storage, organisations can avoid the murky depths of a data swamp, ensuring enhanced security, crystal-clear visibility, and valuable insights from their data lakes.
