5 Big Data Analytics Challenges That Can Cost Time & Money

We are stuck with technology when what we really want is just stuff that works. – Douglas Adams (Author)

This quote sums up the problem most users of business intelligence systems face. Nobody needs to know how to build a car to be able to drive it. Same goes for big data analytics solutions. Why should business users even bother understanding big data analytics when all they want is insights that can keep them on top of their game?

And yet there is no end to the number of times ‘Big Data’ is thrown around at tech conferences, expos and in online/offline publications. It may be one of the biggest buzzwords, but it’s got to the point where it’s as annoying as having a song stuck in your head.

Business users are now more interested in knowing what it can do rather than what it is. Here are some of the top challenges about big data analytics that bug businesses –

Big data talent is hard to come by

Big data is a multi-headed hydra that has the propensity to get techies running like headless chickens. Can’t blame them, cause big data technologies are evolving at a rapid rabbit’s pace. That apart, big data talent is of the burn-a-hole-in-your-pocket variety and business acumen is not guaranteed.

A smart way to get around this challenge is to rely on SaaS tools built by nerds who love tech muck. We at Data Scout are one such team that has taken all the pains so you don’t have to. You won’t have to write a single code to get the insights you want. You can find answers to questions you always wanted to ask but didn’t for the fear of being ridiculed.

Ensuring data quality

Those in the know will tell you that it is easier to slap a tiger than maintain quality at big data scale. Too many wars to be fought on too many sides – data duplication issues, incorrect user input (sometimes intentional), poor IT talent and data variety. The interplay between all of these is such that one tiny deviation can cascade into a domino effect.

Data-Scout is best friends with some highly intelligent big data algorithms that have our back at all times. We know the usual suspects and we know where to find them, which is attributed to human intervention most of the time. Removing humans from the equation is how we have built a business intelligence tool that is smart and slick.

Relying on the IT department can be inefficient

While big IT labels have developed big data solutions, churning insights out of them is not possible without the expertise of the IT department. The only problem with that is that IT folks are busier than elves at any given point of time. Even if you can buy their time, getting big label solutions to work is akin to taking a knife to a gun fight. They cannot match the real-time needs of today’s competitive environment.

Top of the line big data discovery tools like Data Scout are easier to operate than a word processor. Operating such SaaS tools is confined to your mouse operating skills which require you to point, hover, click, drag and drop. It’s the smart way of supporting day to day business decisions. All the data sources you’ll ever need can be added without breaking a sweat.

Development costs are too high

Building a customized big data solution from the ground up is an expensive, not to mention time consuming affair that’ll throw you off your work-life balance resolution. It often involves making hardware and software adjustments, as well as getting the commitment of every business leader in the organisation to collaborate with the appointed technical team.

This is where a plug and play solution like Data Scout makes all the difference.  You don’t have to install any software; all you need is a web browser. Also, SaaS applications like ourselves come at the fraction of the cost of an in-house solution. You can start using it from the moment you subscribe. When you discover how intuitively easy to use Data Scout is, you’ll realize that the cost is a cherry on top.

Lack of dedicated support

One of the biggest challenges of pivoting towards an in-house big-data solution is the lack of dedicated support for the many front-end and back-end big data technologies that come into play. Since most big data technologies are open source and free to use, big data workers rely on crowd sourced answers to their problems on collaborative sites like stackoverflow.com and codeproject.com. In other words, support is weak and not guaranteed.

The biggest advantage of using a tool like Data-Scout is that you or your IT team does not need to bother with such issues. The tool has been developed keeping in mind business users from diverse verticals like manufacturing and retail. We have a team of expert resources that are well ranked in various online big data communities for answers on complex technology integration and deployment issues. As a leading edge SaaS tool, our users have a variety of interactive dashboards at their disposal to tinker around with.

So if you are a business leader who is interested in discovering the endless possibilities of using a big data solution rather than educating yourselves about big data, sign up for our free trial.


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