3 Reasons Most Enterprises Aren't Ready For Advanced Analytics Strategies
May 20, 2016

Dan Ortega
Blazent

Share this

"Data, data everywhere, and not a drop to drink." All businesses are fully aware of how much data they're swimming through on a daily basis. And because its buzzy and trendy, most of these businesses are looking to do more with their data, striving to implement cool sounding technologies like machine learning and predictive analytics.

How many, exactly? 41% of executives in a recent 451 Research survey of advanced analytics are looking to begin implementing applications such as Machine Learning or Predictive Modeling in the next 12 months, and an additional 14% plan to do so in the next 24.

And why shouldn't they? These sophisticated programs are highly efficient and represent the future of many different verticals supported by the technology industry.

Yet as enterprises and their leadership see these initiatives on the horizon, a startling number are overlooking a crucial factor that could make or break the success of these investments: the quality of their own data. With some enterprises curating up to 200 disparate data sources, ensuring data quality is no easy task. But getting it right can literally make the difference between a very public crash 'n' burn, or being the standard that everyone tries to emulate.

Here are three reasons why the average enterprise isn't properly prepared for an advanced analytics strategy.

Reason 1: Medieval Methods for Managing Data Quality

According to the survey, 37% of enterprises employ a manual data cleansing process. Given current data volumes, manually cleaning something isn't so 1990s, it's actually more like 1500s. Many of these enterprises are starting to look towards algorithmic automation – but how can they successfully automate advanced processes when their back-end data quality checks remain manual?

44.5% of respondents are in a reactive mode, meaning they only deal with their data quality when it becomes a problem … that they notice (and by the way, their customers noticed way before they did).

The majority of respondents (65%) acknowledge up to 50% of business value can be lost to poor data quality – think that number is going to decrease when the number of initiatives that rely on clean data increases?

Reason 2: Businesses Don't Know The Exact Quality of Their Data

Because of these current Data Quality Management "strategies", IT departments and C-suite executives have a lack of faith in the actual quality of their data.

Over half (57%) of respondents in this survey were "somewhat confident", "unaware", or "less than confident" in the state of their data. Not exactly a resounding endorsement.

This feeling is compounded by the dependency on manual effort to drive remediation in many enterprises' data quality process. Manual entry was the leading cause of poor data quality, also coming in at 57%.

To be fair, you can't blame employees for making mistakes in data entry or processing, but you can blame their management for not providing them with the right tools to handle the volume of data they face every day.

Reason 3: The Stream of Data Today is About to Become a Tsunami

If proper preparations aren't undertaken right now with the relatively manageable amount of data that currently exists, it will be not just be harder, it will be impossible to get a handle on it at the rate that data sources and volumes will continue to expand over the next 3-5 years.

95% of survey respondents acknowledge they expect data to increase (the other 5% presumably in businesses that won't be around in five years).

70% expect data volumes to grow by 70%, while nearly all of the remaining 30% expect it to grow by more than 75%. Chances are, all of them are underestimating what's headed in their direction.

The problems faced by the enterprise today are significant, but can be managed if IT executives deal with the data quality issue now. Tools and technologies are available to ensure viable data quality, which becomes the foundation for growth and value-add, but the choice to act now or quickly get buried is in our collective face, and requires immediate action.

Dan Ortega is VP of Marketing at Blazent.

Share this

The Latest

October 16, 2017
Hurricane season is in full swing. With the latest incoming cases of mega-storms devastating the Southeastern shoreline, communities are struggling to restore daily normalcy. People have been stepping up and showing remarkable strength and leadership in helping those affected. However, there is another area that we need to remember in these trying times – and that is businesses continuity ...
October 12, 2017

Gartner highlighted the top strategic technology trends that will impact most organizations in 2018. The next trends focus on blending the digital and physical worlds to create an immersive, digitally enhanced environment. The last three refer to exploiting connections between an expanding set of people and businesses, as well as devices, content and services to deliver digital business outcomes ...

October 11, 2017

Gartner highlighted the top strategic technology trends that will impact most organizations in 2018. The first three strategic technology trends explore how artificial intelligence (AI) and machine learning are seeping into virtually everything and represent a major battleground for technology providers over the next five years ...

October 10, 2017
This is the sixth in my series of blogs inspired by EMA's AIA buyer's guide — directed at helping IT invest in Advanced IT Analytics (AIA), what the industry more commonly calls "Operational Analytics." In this blog, I examine scenario-related shopping cart objectives for AIA. At EMA, we evaluated seven unique scenarios relevant to AIA adoptions. Our scenarios included agile/DevOps, Integrated security, change impact awareness, capacity optimization, business impact, business alignment and unifying IT ...
October 06, 2017

In the Riverbed Future of Networking Global Survey, more than half of the respondents acknowledged that achieving operational agility is critical to the success of a modern enterprise, and next-generation networks as well as the technology to support them are key to reaching this goal ...

October 05, 2017

Legacy infrastructures are holding back their cloud and digital strategies, according to the Riverbed Future of Networking Global Survey 2017. Nearly all survey respondents agree that legacy network infrastructure will have difficulty keeping pace with the changing demands of the cloud and hybrid networks ...

October 04, 2017

Digital disruptors are emerging in all industries, and the need for CIOs to embrace digital transformation is urgent, according to Gartner ...

October 02, 2017

Environments indicate "where" the AIA solutions we investigated can be applied. All 13 of the solutions we investigated support cloud for performance, core infrastructure, and application performance and availability. Mainframe had the support of six of our respondents, and IoT and cloud for change and capacity were not yet prime areas of focus for most of the vendors in our AIA buyer's guide ...

September 29, 2017

Cost, overhead, and time to value are often key challenges in adopting AIA solutions. In the past, these factors have often been especially onerous. But we saw strong levels of improvement among many vendors, and surprising areas of innovation among others ...

September 28, 2017
Most senior executives recognize that unified communications and collaboration (UC) are integral applications on the digital transformation path. As a result, many companies are in the process of replacing legacy voice and video infrastructure and disparate messaging and collaboration tools with next-generation UC systems, including cloud-based unified communication as a service (UCaaS). With UC, companies can accelerate time-to-revenue, improve productivity and reduce capex and opex – the three pillars of return on investment (ROI) that drive corporate strategy ...