Real-World Tools to Help Navigate a Data-Driven World - InformationWeek
IoT
IoT
Data Management
Commentary
7/25/2018
08:00 AM
Bill Kleyman
Bill Kleyman
Commentary
Connect Directly
Facebook
Twitter
LinkedIn
Google+
RSS
50%
50%

Real-World Tools to Help Navigate a Data-Driven World

When one cute little source for data gets you thinking about the world of really big data.

It’s been absolutely fascinating to see just how much data we’re creating in today’s world. Let me give you a fun example. About a month ago, I became a new dad! And, already, our baby has a pretty big digital footprint. In fact, I even wrote an entire blog around becoming a cloud-powered parent, utilizing smart tools, analyzing data, and even looking at patterns.

Think it’s crazy? Well, working with data patterns and cognitive systems not only gets me, as a parent a bit of extra sleep, this may very well become the new normal moving forward in our everyday lives.

Image: Shutterstock
Image: Shutterstock

Consider this, cognitive systems can greatly step up the frequency, flexibility, and immediacy of data analysis across a range of industries, circumstances, and applications. IDC estimates that the amount of the global datasphere subject to data analysis will grow by a factor of 50 to 5.2ZB in 2025; and the amount of analyzed data that is “touched” by cognitive systems will grow by a factor of 100 to 1.4ZB in 2025!

Those are some pretty big stats in a world that continues to become even more digitized. But what are the practical applications here? Many organizations certainly know that they have a lot of data; but they don’t entirely know what to do with it.

Earlier this month, I discussed how success with IT initiatives isn't just about creating data; it's about making good use of that data. I covered some real barriers to better data utilization including:

  • Lost data points and silos.
  • Losing control of connected devices
  • Forgetting about security
  • Not understanding the difference between embedded data and productivity data
  • Ensuring infrastructure keeps up with data creation

So, you’re in an organization with a lot of data. You’re housing it in various locations and you have a business initiative to leverage this information to help you make better decisions. This is where lots of folks get stuck. That is…

Step 1: Create data

Step 2: ???

Step 3: Profit

That being said, let’s look at a few tools that can really help you grasp the power of data.

Big data engines. You’ve heard of them and you’ve read about them. But, what is a big data engine? Quite simply, big data engines allow you to examine and analyze large amounts of data. The key purpose is to uncover patterns and insights, and even correlate different types of data points. This is something humans and simple technologies can’t do. Big data engines are, arguably, your starting point for creating business intelligence.

Already, industries all over the world are leveraging big data engines to stay competitive and help them make better business as well as market decisions. There are a few parts to big data. They include data managing, the mining process, in-memory analytics, and the engine itself. This could be Hadoop, MapR, Google Bigdata, Cloudera, Hortonworks, MongoDB, Azure big data and analytics, and many more. The choice of design and engine will really depend on your data set and your own use-cases.

Data warehousing. Oftentimes, when I discuss data warehousing, I get the term "database" thrown in there. Let’s start here, a data warehouse is not a database. Although you could argue that they’re both relational data systems, they absolutely serve different purposes. Data warehousing allows you to pull data together from a number of different sources. The purpose is to help analyze and report on data. Data warehouses store vast amounts of historical data for fast, as well as complex queries, across all data types being pulled together. There are lots of use-cases for a data warehouse as well. For example, if you’re doing very large amounts of data mining and require an intelligent "warehouse" to store all of this data. A data warehouse is far better than a traditional database.

Similarly, if you need to quantify vast amounts of market data in-depth, a data warehouse could help. You can use that data to understand the behavior of users in an online business to help make better decisions around services and products.

While we’re on this topic, you may have heard the term "data lake". This is a newer data processing technology, which focuses on structured, semi-structured, unstructured, and raw data points for analysis. Data warehouses, on the other hand, only look at structured and processed data. Where data warehousing can be used by business professionals, a data lake is more commonly used by data scientists. As far as examples, you can find data warehousing services from a variety of solutions, including Amazon Redshift, Google BigQuery, and Panoply. Data lake examples include Amazon S3 as well as the Azure Blog Storage service.

Data visualization. This data analytics technology is really cool! When you gather all of your data, a key stopping point is the lack of "visualizing" the information in a productive manner. Data visualization allows you to see information as a picture, graph, or illustrated collection of data. The point is that it helps you interact with your data to see new concepts and patterns that were once difficult to grasp. From there, you can drill much deeper into your charts and graphs to really understand how data is changing and impacting your business. Plus, there are some powerful mechanisms that can help with data visualization. They include Microsoft Power BI, Tableau, IBM Watson, SAP Analytics, and Google Analytics.

This next part is important – there are numerous different approaches to data analytics. I didn’t even have time to get into predictive analytics!

The bottom line is that you have options around on-premise architectures, cloud-driven solutions, and the hybrid option as well. The first step in any data journey will be your own exploration of data repositories, how you create data, and the structure of your data. That is, what are the sources, is it structured or unstructured data, and are there governance, compliance requirements, or regulations (GRC) wrapped around it? All of this will dictate the type of solution you’ll leverage and what can be most effective.

Navigating the landscape of your own data really shouldn’t be a solo journey. This is a big reason why there are entire professions around data science and analytics. Be sure to leverage these experts to help you get the most out of your own data sets.

See what else is going on in the world of big data analytics:

Algorithmic Commerce Takes Off, Aided by Humans

Data Science Talent Shortage Drives Demand for Contractors

CDAOs Drive Change by Blurring Lines, not Drawing Them

5 Top Languages for Machine Learning, Data Science

 

Bill is an enthusiastic technologist with experience in a variety of industries. This includes data center, cloud, virtualization, security, AI, mobility, edge solutions, and much more. His architecture work includes large virtualization and cloud deployments as well as ... View Full Bio
We welcome your comments on this topic on our social media channels, or [contact us directly] with questions about the site.
Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
2018 State of the Cloud
2018 State of the Cloud
Cloud adoption is growing, but how are organizations taking advantage of it? Interop ITX and InformationWeek surveyed technology decision-makers to find out, read this report to discover what they had to say!
Register for InformationWeek Newsletters
Video
Current Issue
The Next Generation of IT Support
The workforce is changing as businesses become global and technology erodes geographical and physical barriers.IT organizations are critical to enabling this transition and can utilize next-generation tools and strategies to provide world-class support regardless of location, platform or device
White Papers
Slideshows
Twitter Feed
Sponsored Live Streaming Video
Everything You've Been Told About Mobility Is Wrong
Attend this video symposium with Sean Wisdom, Global Director of Mobility Solutions, and learn about how you can harness powerful new products to mobilize your business potential.
Flash Poll