Don’t Let Data Collect Digital Dust: Creating Competitive Advantages through Data

Before we get into the power of data, it’s important to understand just how much data we’re creating. A recent report from Cisco indicates that globally, the data stored in data centers will nearly quintuple by 2021 to reach 1.3 ZB by 2021, up 4.6-fold (a CAGR of 36%) from 286 EB in 2016.The report goes on to state that big data will reach 403 EB by 2021, up almost 8-fold from 25 EB in 2016. Big data alone will represent 30 percent of data stored in data centers by 2021, up from 18 percent in 2016.

Finally, according to a report by IDC, by 2025, embedded data will constitute nearly 20% of all data created — three quarters the size of productivity data and closing fast. Productivity data comes from a set of traditional computing platforms such as PCs, servers, phones, and tablets. Embedded data, on the other hand, comes from a broad variety of device types, including:

  • Security cameras
  • Baby monitors
  • Smart meters
  • Chip cards
  • RFID readers
  • Fueling stations
  • Building automation
  • Smart infrastructure
  • Machine tools
  • Automobiles, boats, planes, busses, and trains
  • Vending machines
  • Digital signage
  • Casinos
  • Wearables
  • Medical implants
  • Toys

As the report points out, the average rate per capita of data-driven interactions per day is expected to increase 20-fold in the next 10 years as our homes, workplaces, appliances, vehicles, wearables, and implants become data enabled.

Do you have any of these data-creating sources in your environment? Maybe you have something else that's creating vast amounts of data. The big question is pretty direct - what are you doing with it all? Or, is it just being 'stored' and collecting digital dust? Let's look at a few approaches that allow you to leverage the power of data and even create competitive advantages!

Basically, data visualization allows you to present data as a picture, or even an easy-to-consume graph. From there, it allows it and business leaders to make better decisions based on the analytics presented visually. Because data can be dirty, this helps them grasp challenging market or business concepts as well as identify new patterns. Furthermore, data visualization can be interactive. Basically, once data is visualized, you can drill down even further into charts and graphs and see the way data changes as it’s processes and analyzed against various scenarios. So, after the data has been processed and saved according to your requirements, you can analyze the data.

Solutions like Panoply can connect to many data visualization tools, from Tableau and Looker to iPython notebooks and R. As long as the visualization tool has an ODBC, JDBC, Postgres, or AWS Redshift connection, it can connect immediately to Panoply.

From a business or IT perspective, data warehouses pull together data from many different sources within an organization for reporting and analysis. The reports created from complex queries within a data warehouse are used to make business decisions much more accurately and in real-time with market requirements.

Data driven decisions aren’t just a trend. In fact, insight and analysis help drive the bottom line and improve business efficiency. Teams committed to forward movement, innovation, and growth use analytics in daily operations to enhance their competitive stance and improve their organization. Leveraging big data as well as data analytics, you can automatically transform your data into valuable insights. Whether it’s structured or unstructured data, coming in from various sources; leveraging big data as well as data analytics solutions will help you visualize this data and make it much more actionable.

The main point here is not to just sit there and accumulate data. You really need to put this information to work. It’ll benefit your users, your business, and really help you differentiate in the market. Also, getting started doesn’t have to be hard. Designing solutions around data warehousing and even data visualization must start with an exploration of your current data repositories and storage architecture. From there, you can isolate key data points and design a data analytics solution that can really help your organization evolve.

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