data analytics data engineering data science

The Challenges Businesses Face With Data Analytics

Before businesses implement data analytics into their businesses they first need to understand the challenges ahead of them.

In a recently released NEC report, Taming Your Data Assets and Delivering Real Business Outcomes, it highlights a number of roadblocks companies need to identify and understand.

These include,

  • The sheer volume and variety of data sources which need to be corralled;
  • No coherent, scalable data infrastructure to provide a comprehensive view of the data;
  • Integrating disparate sources of data;
  • An inability to analyse the internal and external data for strategic decision-making;
  • Poor data governance and a lack of defined policies for quality management; and
  • A lack of qualified professionals with the necessary skills sets to harness big data and analytics tools effectively.

Organisations have a long history of managing the structured data that falls out of ERP, CRM and marketing applications.

Systems for managing unstructured data such as documents, videos or sound recordings, and even log files, have matured in recent years — as have solutions for data compression in response to the explosion of new data sources, the report noted.

And while data warehouses have been around for decades, data lakes have emerged as a way to consolidate both structured and unstructured data.

Despite this, seldom companies have managed to master these ever-growing sources of data.

The authors of the report note this is a problem which prevents them from obtaining a 360-view of their customers.

For example, while a customer name might be stored one way in one system, it might be recorded slightly differently in another, even though it represents the same person.

The best outcome for both the customer and the organisation is achieved by consolidating the view across all of these entities in a way that provides the richest and most complete picture of interaction with the customer.

Data Maturity

While businesses understand the power of data analytics, there is a huge variation when it comes to how far along the data analytics maturity curve organisations have ventured.

The report explained the different maturity journeys businesses are on when it comes to their data analytics.

There are typically three stages companies fall under when it comes to their data maturity.

Firstly those at the start of their journey may well have discussed big data, but its potential is not really reflected in business objectives or strategies. Typically, such organisations lack a single coherent data architecture, the report explains.

The second stage is those companies that may have developed a standard architecture, but find it lacks scalability and cost-effectiveness.

Thirdly, those who are further along, and have started implementing a data framework such as Hadoop, may lack a robust big data governance and security framework.

These organisations need a way forward that defines the journey towards data analytics maturity and enables them to gain better business insights from a clearer understanding of the needs of their customers.

Once businesses identify and understand their challenges they can then begin implementing data analytics.


Author: Athina Mallis

Recommended posts

Empowering women to code: Coding academies vetted by Digital Source

According to Forbes, women represent 26% of all positions in the tech industry and only about 16% at the executive level. As specialists in

What is a Data Catalog? Value, Benefits, and Features

No matter where data comes from, becoming data-driven depends on every member of your organization being able to find, access, and use the data
New podcast: An Interview with Tom van Wees and Roderick de Koning, CCO and CEO of Ginger Payments