What to Expect in Data and Analytics in 2020
Data and analytics professionals should consider these three actions to proactively plan and prepare for key 2020 trends.
- By Heine Krog Iversen
- January 7, 2020
In 2019, we started to see a significant acceptance and movement to the cloud by a growing number of companies. The cloud has clearly become the primary hosting place for analytics, data, and AI.
Moving to the cloud provides organizations better scalability for both storage and computing. The cloud also provides a foundation for accelerating adoption of new technologies and for achieving greater organizational efficiency such as automation.
With 2019 in our rearview mirror and as we welcome in 2020, let's take a look at some of the possible new business shifts that I believe could occur in the market and what professionals in the data and analytics field can do to prepare.
1. More use cases show us that the ever-growing complexity of the data landscape will continue to emerge as the number of data sources grow and as the lifespan of data sources shrink. Further blending of technologies will continue to occur -- specifically, blending structured and unstructured data will result in new use cases.
2. The industry will continue to move quickly to adopt new technologies for managing data and analytics. Organizations cannot afford to get stuck with a technology they cannot upgrade or that requires significant rework to modernize. They need to keep up with changing technology, and for this reason speed will dominate. Those looking to play it safe, stay idle, or slow down technology advancement may very well fall behind.
3. The patience on the business side to wait for relevant data is shortening and will continue to do so. Organizations cannot afford to make stakeholders wait for data. Conversely, stakeholders continue to request instant access to relevant data.
There are several reasons I see these trends continuing to have an impact 2020.
First is the forthcoming launch of Microsoft Azure Synapse Analytics. This capability will demonstrate the importance of shortening cycles for data. In fact, in this article posted on the Microsoft site, the company said that "this new offering will help customers put their data to work much more quickly, productively and securely by pulling together insights from all data sources, data warehouses and big data analytics systems."
The company further stated that "with deeper integration between Power BI and Azure Machine Learning, Azure Synapse Analytics can reduce the time required to process and share that data, speeding up the insights that businesses can glean."
Second, the acquisition of multiple visualization and BI tools by large software companies such as Tableau by Salesforce will further expand the importance of analytics data platforms and corporate digital transformation.
Finally, I believe we will see the emergence of DataOps -- a set of principles and processes designed to improve the quality of data and shorten the time required to get data ready and in the hands of users. Automation will play a key role in accelerating data availability and improving data operations.
Preparing for 2020
With these trends in mind, I recommend the following actions be considered by data and analytics professionals to proactively plan and prepare for shifts on the horizon.
1. Change your mindset
To get the most value from all the new tools and technologies, your organization needs to change its approach to preparing data. Because so many organizations are still approaching data with the assumption that data pipelines must be hand-coded, they're wasting valuable resources doing so and should take advantage of automating the process.
Your organization needs to do more with the resources you have, but will incremental steps won't be enough. You'll need a significant change in mindset about how your enterprise executes analytics, BI and AI projects.
To make this happen, spend more time thinking about the why and the what concerning your data and not about how the hardware will be used to get the data in place.
2. Consider rules and procedures
Your organization needs to adapt to new technology, but compliance, legal, and procurement issues or processes often block new technology use because your business doesn't understand it or doesn't have an internal procedure in place for it. It can take months to get a new piece of data into production for analytics, and these rules can prevent your company from maximizing the value derived from new data. Plan for agility and speed but also account for quality and compliance.
3. Think beyond 2020
Although the need to use data efficiently and effectively does not change, the technology around it does. This is especially true for data platforms, databases, data sources, and data elements. Organizations should look for ways to abstract the preparation of data from its format, ensuring that new platforms can be supported as they become available. Those providing access to meet current data needs should also anticipate and try to accommodate future data needs so they can ensure that data requests down the line are faster and easier to fulfill.
Automation to Advance Data and Analytics
Building out a data estate for enterprise analytics has been a growing frontier for the use of automation in recent years. Corporate data estates are the one place where tools typically still result in a lot of hand-written code, which drains resources and is inherently inefficient. The time has come for this to change, and I expect the industry to continue to accommodate and aggressively adopt data automation.
Heine Krog Iversen is the CEO of TimeXtender, a recognized global software company enabling instant access to any type of data in the organization to support advanced analytics and artificial intelligence (AI). Heine can be reached via email.