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Askdata offers a natural language search engine for internal data that translates words into SQL queries.

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Businesses Have Plenty Of Data, So Why Aren’t They Using It?

Dec 6, 2019

In this special guest feature, Simone Di Somma, Founder and CEO at Askdata , believes that businesses already collect so much data in the course of their day-to-day operations. But they could start using that data more effectively by bringing it out from behind the curtain, presenting employees across the board with easy access and interaction for it. Askdata is a startup specialized in the application of Artificial Intelligence (AI) to improve how enterprises consume Analytics. Before founding Askdata, Simone worked at Philip Morris and Hewlett-Packard across Europe, Middle-East and the US with a primary focus on Advanced Analytics. Simone has been a passionate speaker at various events about the benefits of AI and how this technology will transform the way enterprises do their business. When employees have better accessto data, they end up making better decisions. Companies across sectors arealready well in the habit of collecting relevant historical and business datato make projections and forecast the unknown future. They’re collecting thisdata at such a scale that “big data” has become a buzzword technology. Theywant lots of it because they want an edge wherever they can get it — whowouldn’t? But it’s not only the quantity andquality of the data a company collects that play a pivotal role in how thatcompany moves forward — it’s also a question of access. When businessesdemocratize access to that data such that it’s accessible to workers throughouta hierarchy (and those workers end up actually interacting with it), itincreases the quality of decisions made on lower rungs of the ladder. Thosedecisions end up being more often data-informed, and data is power. But that’s easier said than donelately. Businesses have no issue collecting data nowadays, but they do tend tokeep it cordoned off. Data Sticks to the Top of a Business Hierarchy A business’s C-suite (often withhelp from a technical data science team) makes the big-picture decisions thatguide the company’s overall development. This means the employees using data toinform a chosen course of action (like last year’s revenue versus this year’s revenue,or a certain client’s most common order) are either highly ranked within thecompany, or are wonky data specialists. Data lives behind a velvet rope, so tospeak. But this data would be eminentlyuseful to people throughout an organization, regardless of their rank ortenure. Such a level of access would make it more likely that data guides everydecision, and that would lead to more desirable business outcomes over time. Itmight even overtly motivate employees by subtly reinforcing the idea that resultsare tracked and measured. Data Tends Not to Trickle Down to the Appropriate Sources Who better to have a clear view ofthe business landscape than the employees who toe the front lines everyday? What would change if disparateemployees scattered throughout an organization suddenly had access toactionable data points? These are the people positioned to actually make atweak or optimization from the get-go. Whoever comes up with a data-informedstrategy on a strong way forward, these are the people actually implementingit. But an organization-level awareness of an actionable data point doesn’tnecessarily equate to action. As previously established, data hasa high center of gravity. It is managerial food for thought on the way todesigning and executing longer-term business strategies. But when companies change theirculture around access to data and make it easy for everyone to interact withdata, they make every worker think like such a strategist. By the Time a Piece of Data Reaches an Appropriate Source, it’s not Necessarily in a Form He or She Can’t Interact with or Understand As much as managers might like tothink otherwise, there are people in their organization thinking in less thangranular terms. They aren’t necessarily thinking about the costs their actionsmay or may not be having on the company, they don’t think about the overallbottom line. That’s why it’s important that data be in a form that people canuse or understand, because it doesn’t always reach them that way. Getting data into a useable,understandable form happens by preserving connection between departments andavoiding disconnects. There Seems to be a Big Data Disconnect at the Intersection of Engineering and Product Development This is the intersection is where abusiness’s technical prowess meets its ability to design a great product. Whilethe two pursuits are clearly related to one another on the way to great productdesign, it’s rare that one person should excel at both. The people who designgroundbreaking computer algorithms aren’t necessarily the people who design agroundbreaking consumer product, and vice versa. They need each other’s help tounderstand each other. But data is the shared languagethat makes understanding possible. Not everyone has years of data sciencetraining, not everyone has business leadership experience, but even people doingmenial things can still benefit from great access to data. Coming across theyear’s growth goal, for example, might trigger a needle-moving idea fromsomeone on how to actually get there. Great things happen when employees builda shared understanding of the raw numbers that drive everything they do. Businesses already collect so muchdata in the course of their day-to-day operations. But they could start usingthat data more effectively by bringing it out from behind the curtain,presenting employees across the board with easy access and interaction for it.The motivation for doing so should be clear: when more people think about thesame problem in the same terms, that problem is more likely to be solved. All they need is access to the data that makes it possible. Sign up for the free insideBIGDATA  newsletter . This new technology guide from DDN shows how optimized storage has a unique opportunity to become much more than a siloed repository for the deluge of data constantly generated in today’s hyper-connected world, but rather a platform that shares and delivers data to create competitive business value. The intended audience for this important new technology guide includes enterprise thought leaders (CIOs, director level IT, etc. ), along with data scientists and data engineers who are a seeking guidance in terms of infrastructure for AI and DL in terms of specialized hardware. The emphasis of the guide is “real world” applications, workloads, and present day challenges.

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