"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.
Organizations that are working with artificial intelligence (AI) or machine learning (ML) have, on average, four AI/ML projects in place, according to a recent survey by Gartner, Inc. Of all respondents, 59% said they have AI deployed today ...
The 11th anniversary of the Apple App Store frames a momentous time period in how we interact with each other and the services upon which we have come to rely. Even so, we continue to have our in-app mobile experiences marred by poor performance and instability. Apple has done little to help, and other tools provide little to no visibility and benchmarks on which to prioritize our efforts outside of crashes ...
Confidence in artificial intelligence (AI) and its ability to enhance network operations is high, but only if the issue of bias is tackled. Service providers (68%) are most concerned about the bias impact of "bad or incomplete data sets," since effective AI requires clean, high quality, unbiased data, according to a new survey of communication service providers ...
Every internet connected network needs a visibility platform for traffic monitoring, information security and infrastructure security. To accomplish this, most enterprise networks utilize from four to seven specialized tools on network links in order to monitor, capture and analyze traffic. Connecting tools to live links with TAPs allow network managers to safely see, analyze and protect traffic without compromising network reliability. However, like most networking equipment it's critical that installation and configuration are done properly ...
The Democratic presidential debates are likely to have many people switching back-and-forth between live streams over the coming months. This is going to be especially true in the days before and after each debate, which will mean many office networks are likely to see a greater share of their total capacity going to streaming news services than ever before ...
Monitoring of heating, ventilation and air conditioning (HVAC) infrastructures has become a key concern over the last several years. Modern versions of these systems need continual monitoring to stay energy efficient and deliver satisfactory comfort to building occupants. This is because there are a large number of environmental sensors and motorized control systems within HVAC systems. Proper monitoring helps maintain a consistent temperature to reduce energy and maintenance costs for this type of infrastructure ...
Shoppers won’t wait for retailers, according to a new research report titled, 2019 Retailer Website Performance Evaluation: Are Retail Websites Meeting Shopper Expectations? from Yottaa ...
Customer satisfaction and retention were the top concerns for a majority (58%) of IT leaders when suffering downtime or outages, according to a survey of top IT leaders conducted by AIOps Exchange. The effect of service interruptions on customers outweighed other concerns such as loss of revenue, brand reputation, negative press coverage, or the impact on IT Ops teams.
It is inevitable that employee productivity and the quality of customer experiences suffer as a consequence of the poor performance of O365. The quick detection and rapid resolution of problems associated with O365 are top of mind for any organization to keep its business humming ...
Employees at British businesses rate computer downtime as the most significant irritant at their current workplace (41 percent) when asked to pick their top three ...