Organization strategy

Tips for improving the use of data analytics in your organization

It is necessary to use different types of tools. These tools mainly focus on the huge problem of data consumption.

Fremont, California: Companies of all sizes and in all industries are trying to use data to achieve their strategic goals, whether it’s increasing productivity, profitability, risk tolerance, preparedness, sustainability or adaptability in a constantly changing environment. To be agile and resilient, business analytics must evolve with the business and its requirements. Otherwise, it will be hindered or triggered.

Technical debt accrued over years of finding workarounds and filling gaps in old procedures often seems too costly and difficult to remove and replace with more proficient contemporary tools and processes. But the need for sophisticated, modern data analytics has become too great to ignore. The three recommended ways to increase the use of your business analytics and get a return on investment with a business analytics program are:

Get all the data under management

If maintenance is not up to standard, corporate data, the basis for analysis, may only be useful for extremely specific interests. The data is in a platform which can be useful because it is under management. The platform has been created, is in the process of being created, or at the very least it interfaces with such a platform intended for wide access. This indicates that the data is generated considering the data warehouse(s), data lake(s), operational center(s), and master data management center(s). The exploitable platform should be the first choice. Nevertheless, there are several reasons why an application’s data might not be entirely in one of these structures, related to security or to certain data transformations requested by the program. Make sure users don’t create the only data store for components that can’t be used elsewhere, because all business data elements need to be on one platform that can be useful anywhere.

Big Data tools for Big Data

In the past, companies have made costly and ineffective attempts to force large, unstructured data into relational data warehouses. Using the right tools for this data is crucial because the competitive horizon is currently heavily tilted towards big data analysis with the assumption that other data is already in excellent shape. Therefore, it is necessary to use different types of tools. These tools mainly focus on the huge problem of data consumption.

Mastering the shift to a culture of analytics

Change management is necessary to successfully implement self-service and analytics in all business processes. Users go from accepting the change to rejecting it, regardless of the instructions of the leaders. Most late adopters need space or time. They require instances of peers using the analysis successfully. Any cultural direction focused on data or analytics needs to be strengthened for them. The use of self-service analytics is necessary and inevitable to strengthen the foundation of business today.