Four signs your business needs a data lake , now
It is now well known that the digital universe , which comprises most businesses ’ data needs , is growing exponentially . In fact , over the next decade the digital universe is expected to grow by around 40 percent a year . This is growth at an astonishing speed .
In this environment , it is critical that businesses use data analytics to enhance competitiveness and meet the needs of the ‘ information generation ’; millennials and more born into the digital era . From helping to predict buying behaviours , to driving innovation projects that will enhance customer service or improve business productivity , data lakes that can collate , store and analyse vast amounts of data have great power to transform a business for the better . Analytics should no longer be an aspiration , but a necessity .
So , how do businesses know when they need to scale-up and invest in a data lake ?
There are four tell-tale signs :
1 . Operational complexity : In a pre-data lake environment , if a business is trying to scale its infrastructure there ’ s a good chance that their data requirements will outstrip their ability to manage them . To cope with operational complexity , businesses would require a more flexible common storage resource , i . e . a data lake .
2 . Operational cost : When a company finds that business demands on IT keep growing even when it is trying to reduce OpEx . It is time to look at a new approach . Businesses need to invest in additional third party support to monitor , manage , deploy and improve their systems than simply adding headcount .
3 . Production strain : Another key indicator of the need for a data lake is when existing analytics applications are putting a strain on the production systems of a business . Real-time analytics can be extremely resource-intensive .. Data lakes are key to ensuring that real-time analytics can run at optimum performance .
4 . Multiprotocol analytics : A final key indicator that a business needs a data lake is when data scientists are running apps on a variety of different Hadoop distributions and need to hook their data up to them . Businesses will need multiprotocol support in the future as analytics experimentation carries on , and they need to plan for this with a data lake strategy .
Across the industries , from finance to retail , manufacturing to media companies , each thinks that their problems , challenges and opportunities are unique . But , when you abstract the specifics you ’ ll always come back to the same universal challenges . What unifies and characterises all of these is the transformation brought about by information technology and the potential of big data .
Not every business will be ready to deploy data analytics yet , but most will , at the very least , need to start planning for it or risk losing out to competitors that embrace the technology . Because , eventually all businesses will need to embrace data analytics , and those that don ’ t will fade into obscurity .