Modernizing to Deliver Data-Driven Capabilities

IT executives and line-of-business experts understand the importance of data for their success and are adopting modern technologies to enable the delivery of timely data and insights to enhance decision making. In line with their data-driven goals, organizations are leveraging hybrid and multi-cloud strategies. However, they are also finding that cloud approaches add their own complexity.

There are numerous business objectives that are driving data strategies, but the most often mentioned are improving the decision making of end users, and uncovering customer preferences and patterns.

Top 5 Business Uses Driving the Data Strategy

  1. To inform decision making
  2. To understand customers and trends
  3. To improve internal operations
  4. To provide smarter services and products
  5. To support a better customer experience

Adoption of machine learning has almost doubled over the past year, with use cases including both internal efficiencies and business growth initiatives. However, challenges with access to the right data and a lack of operational automation have been seen.

Top 5 Business Drivers for Machine Learning Projects

  1. Operational improvements
  2. Security and risk
  3. Customer retention
  4. Revenue growth
  5. Accelerate innovation

Source: “Profiling the Data-Driven Business, 2019,” produced by Unisphere Research, and sponsored by Pythian

Implementing a successful hybrid cloud strategy is challenging for organizations.

Key hybrid cloud problems include:

  1. A lack of consistency between cloud platforms
  2. Need for additional training and skill sets
  3. Difficulty in porting data and applications

86% of enterprises are considering or have already “repatriated” one or more workloads from the public cloud back to the data center, showing that many are still in the early phase of cloud adoption.

Source: IDC white paper: “Benefits of the Consistent Hybrid Cloud: A Total Cost of Ownership Analysis of the Dell Technologies Cloud,” sponsored by Dell EMC

There are not enough on-premise resources to keep up with the growth of data management requirements. This means that cloud services are increasingly being tapped as a vital resource in the data manager’s toolkit.

For their latest database projects, respondents to a survey were close to evenly split between deploying on cloud or on-premise, with a bit more emphasis on on-prem.

  • 44% deployed their projects in the public cloud or as part of a hybrid architecture.
  • 52% indicated their most recent database project involved an on-premise implementation.

A combination of scalability, cost, and maintenance benefits are driving public cloud deployments.

  • Greater scalability is the #1 advantage.
  • Lower cost is seen as the #2 advantage.
  • Reduced need for infrastructure maintenance comes in at #3.

Source: “2019 IOUG Databases in the Cloud Survey,” produced by Unisphere Research and sponsored by Amazon Web Services

Organizations are strongly positive about the cloud, but also concerned about the slow pace of analytics adoption in the cloud.

  • 83% agree that public cloud is the best place to run analytics.
  • 91% say analytics should be moving to the cloud faster.
  • 69% want to run all of their analytics in the cloud by 2023.

Source: “The State of Analytics in the Cloud,” conducted by Vanson Bourne on behalf of Teradata

Hybrid cloud, using a combination of public and private, is the focus for many enterprises, and along with that, they are keenly focused on cost optimization.

  • Organizations leverage almost 5 clouds on average: Respondents are already running applications in a combination of 3.4 public and private clouds, and experimenting with 1.5 more for a total of 4.9 clouds
  • The #1 priority in 2019 is cloud cost optimization. Optimizing existing cloud use is the top initiative in 2019 for the third year in a row, increasing to 64% from 58% in 2018.

Source: “RightScale 2019 State of the Cloud Report” from Flexera



Newsletters

Subscribe to Big Data Quarterly E-Edition