Now Reading
Five key challenges to data analytics in a hybrid environment
[vc_row thb_full_width=”true” thb_row_padding=”true” thb_column_padding=”true” css=”.vc_custom_1608290870297{background-color: #ffffff !important;}”][vc_column][vc_row_inner][vc_column_inner][vc_empty_space height=”20px”][thb_postcarousel style=”style3″ navigation=”true” infinite=”” source=”size:6|post_type:post”][vc_empty_space height=”20px”][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row]

Five key challenges to data analytics in a hybrid environment

Business success is often tied to the ability to unlock the power and potential of data. First, you need to FindData is becoming increasingly complex in today’s complex environment, making it more difficult to access the data.

Anthony Nornabell, Director at HPE Canada’s GreenLake Cloud Services at the CanadianCIO Virtual Roundtable, stated that data is only half the story. According to him, data could be located at the edge or in the cloud in modern architectures. To be able access the data and gain insights from it, you must understand where it is.

Participants to the Roundtable said that they are keen for their organizations’ data-drivenness. According to a technology executive from the financial sector, it’s about getting data into the hands of those who need it to make timely decision. Like many others, they acknowledge that they are still facing numerous obstacles to their success.

Five challenges to getting value from data

Although they acknowledged that there are many challenges in extracting business insight from their data, the CIOs focused on five key themes.

  1. Large data sets in different places. Participants noted that the volume of data is overwhelming. Furthermore, the fact that it exists in multiple systems only makes it more complicated. According to Dilip Ramachandran (Senior Director of Marketing with AMD), silos for data and analytics are common in large organizations that have different business units.
  2. Data quality. Harmonizing data collection for analysis is a huge challenge. One CIO stated that his company spent 18 months trying to get different business units to agree on the data fields.
  3. Resources. Nornabell said that there is a lot of movement on the labour market at the moment. It is difficult to keep the skills-sets necessary to manage the infrastructure. It is also difficult to find and keep qualified and experienced staff. This makes it crucial that they are focused on the top business priorities and the right tasks.
  4. Data literacy. Participants said that they still struggle with convincing people of the power and truth of data. One technology leader said that people still want to see data confirm their expectations. Data is able to uncover hidden patterns, which is the power of data. It is about data telling us what we don’t know, not what our already know.
  5. Data sensitivity and compliance. If it isn’t done correctly, the classification of sensitive data can be a problem. One CSO noted that it is important to identify the location of sensitive data in order to comply with regulations.
Avoiding the data swamp

Participants stated that they are focusing on creating a single source of truth to help them gain more control over their data. One executive in the financial industry noted that the ultimate goal is to have a 360-degree view on the customer and all products they have bought.

Nornabell said that technology allows organizations to access their data from anywhere. GreenLake’s platform, for example, offers the cloud experience, whether it is in infrastructures edges, colocations or data centres. He stated that organizations can combine the agility of cloud with the security and reliability of on-premises facilities. They don’t have to compromise cloud agility if they need data on-premises. They are in control of their data and can make strategic choices about where it is stored and how it is processed.

It’s also essential to establish clear ethics and governance procedures. One executive noted that even with centralized data, people often extract the data and then work in silos. He stated that it is important to have a solid governance program in place to establish clear rules for how Governance works with centralized data. This will ensure that everyone can trust one data set. If governance is poor, large data lakes become swamps.

View Comments (0)

Leave a Reply

Your email address will not be published.