If someone asked you to explain – in just two words – how an organization can succeed in today’s ultra-competitive world, it would be tough to beat efficient productivity.
They relate directly to the fleeting resource we all know well: time. We know that when we’re good stewards of our time, we’re already ahead in the game. We also know technology has proven to be a practical tool that fuels efficient productivity.
Today another important technology enabler has emerged – one that’s revolutionizing efficient productivity. It’s called augmented data & analytics, and simply put, it’s helping organizations achieve their objectives faster and cheaper. More specifically, augmented data & analytics uses artificial intelligence (AI) and machine learning (ML) to automate many of the time- and resource-intensive data management and data-science tasks that consume the majority of a data worker’s time.
Types of Tasks that Can Be Automated
- Data profiling and cleansing
- Data association, categorization, and cataloguing
- Performance tuning and database configuration optimization
- Natural language data search and results interpretation
- Predictive insights and recommendations
Benefits of Augmented Data & Analytics
- Improved operating efficiencies
- Increased data accessibility
- Increased productivity for data workers
- Reduced operating costs
- Undiscovered business insights
The Future is Now
As you read and learn more about it, you’ll notice that augmented data & analytics can and does perform some tasks that humans do. This, of course, is something that’s been predicted for many years. Now that future is here.
Global research firm Gartner reports that by the end of 2022, more than half of data & analytics services will be performed by machines instead of humans.
That might sound scary, but in reality, what those machines will replace are repetitive, manual tasks, leaving higher-value analytical and interpretative data tasks for humans. So augmented data & analytics are actually complementary, and ultimately makes data workers more productive.
A Real World Example
Today, data privacy regulations not only require organizations to know where and how they store all personal information on employees and customers, but also to provide that data upon request, and if asked, to delete that data within defined timelines. This personal information can reside in thousands (if not tens of thousands) of data repositories across an organization – many of which can be undocumented.
Without augmented data & analytics, it would literally take years to inventory that much personal data, let alone keep it updated. Fortunately, AI “crawlers” make complying with these regulations easier because they can identify, categorize, and catalogue all personal data – sometimes in hours, and at most, in weeks instead of years. The end result? Personal information is available in seconds or minutes of a request versus days, weeks, or months.
So, yes, potentially from years to hours and from months to seconds, that’s the power of augmented data & analytics. It’s also what we call efficient productivity.
What adjective is your organization putting in front of productivity? If it’s not efficient, we suggest you take a closer look at augmented data & analytics as a tool that can help enable the future you desire.
Pero Dalkovski has spent his career delivering data and analytics consulting services that drive business value. He currently co-leads RevGen’s Analytics and Insights services.