Data-Driven Decisions with Analytics

With over 175 Zettabytes of data predicted to exist by 2025, every organization has piles of data. But harnessing all that information for the data-driven decision making needed to gain a competitive advantage and glean insights is the real challenge.

Article: Next-Gen Business Analytics Tools

The first step in creating a data strategy is identifying what type of data culture you have. Are you and your team data literate? Are you using your data in a meaningful way to have conversations cross-organizationally? Leveraging our onsite and virtual workshops, our Analytics team can help you understand where your data is coming from, who has access to it, and how to harness it.

Start making data-driven decisions by leveraging analytics. Contact us to learn more.

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IT Operational Analytics

Your data is growing. The ability to identify use cases for your data is a key way to get real answers to problems and create more efficient workflows. However, there is a challenge: how can a business organize and gain insight into data being created every second of every day? What about unneeded data, that only distracts from potential solutions?

Leveraging IT operational analytics can help. For example, machine learning for predictive analytics in IT can address common pain points using both live and historic data. This empowers your business gain real insight in real time.

Examples of IT operational analytics benefitting businesses include:

Identifying if customers are having trouble transacting.
Correlating data across multiple data centers to provide insights.
Ingesting data across an airport to determine best traffic patterns for luggage.
Identifying and evaluating data from POS and human resource systems to optimize hours for capital resources.

Learn more about how IT operational analytics works by reading some case studies below:

Case Study: Analytics Takes Field at Oregon State University

White Paper: Analytics Yields Actionable Insights for Retailers

Blog Post: Start Your Data Strategy by Identifying Your Goals

Use Case: Security - Keeping your organization secure means protecting it from outside attackers. Threats such as next-level phishing and voice impersonations are enhanced through AI being leveraged by bad actors, increasing the efficiency of the attack when compared to more traditional social engineering attacks.

Artificial Intelligence and Machine Learning

The more data that continues to flow into organizations, the more organizations are going to need tools to harness and effectively leverage that data. Artificial intelligence and machine learning tools address the influx of data by being able to compile the information in faster and more intelligent ways, evaluating the information and offering correlations. These systems can automatically improve as they learn from the data they collect, reducing the need for manual programming and human effort. This creates opportunities for improved customer engagement and enhanced operational procedures.

Blog Post: AI-Powered Operational Analytics is the Future - the Future is Now

Business Intelligence

Using historical and current data, business intelligence (BI) drives operational efficiency and strategic growth — if organizations know how to harness their information. One of the biggest challenges with BI analytics is that organizations may not being meaningfully utilizing their tools to make actionable decisions — leaving them wondering why they’re not getting desired results.

Learning how to build a meaningful business intelligence strategy requires an understanding of your own goals, your data and the tools you’re using. Read below to understand how BI analytics have helped a water advocacy group. Work with us to start building a strategy that meets your organizational and industry needs.

Use Case: Using Microsoft's BI Analytics Tool for Water Advocacy

Data Management

Data is coming in larger quantities and can provide more insights than ever before. Organizations must know where their data is coming from, how they’re visualizing the data, what tools they’re using and how they’re sharing the data before they can even consider meaningful utilization to make actionable decisions.

Managing your data is the first step in properly utilizing analytics. If your data is scattered and unorganized, you’ll be limited in your ability to make decisions. Learn how data management impacts your analytics initiatives, and how you can better manage your data in these case studies and articles.

Blog Post: Data Powers Digital Transformation

Check in machine at Oslo Gardermoen International Airport

Use Case: Internet of Things – The influx of new data is partly in thanks to new technologies, and there may be no better example of that than the Internet of Things. Data coming from IoT devices can teach organizations new information about their customers – from how they interact with a product to how they might use it.

Data-Driven Decision Making with CDW + Partners

We are invested not just in the technology of today, but in what the industry is looking to do tomorrow and five years from now. That's why we've partnered with leading organizations to help you with your analytics initiatives. We offer years of experience in helping our customers choose the right technology in tandem with the right professional services from CDW and our partners.