Most business leaders will agree that data analytics is a strategic necessity today. Without access to comprehensive data and effective ways to interpret it, organisational decision-makers may find themselves relying solely on intuition while navigating unfamiliar roads in the dark.
Gut-based decisions can occasionally lead to success, however, those wins are often more coincidental than a reflection of true strategic insight.
More than 90% of the businesses derive benefits from data analytics strategies
A robust data analytics solution enables businesses to transform raw data into organised, actionable insights across numerous functions. They can span CX—helping personalise interactions based on an analysis of individual preferences and behaviours, growth strategies—allowing teams to identify distinct customer segments basis emerging deal patterns, post-sales support—enabling quick response times by analysing ticket allocation systems and discerning gaps, and so on. It’s no surprise, then, that nearly 92% of organisations reported measurable value from their data and analytics investments in 2023.
Unfortunately, many organisations fail to derive full value from their data analytics strategies. One of the reasons for that is analytics systems not having a full view of what’s happening across the company owing to data silos.
Information silos can affect the quality of data insights
There are numerous reasons why an organisation can end up with fragmented or siloed data, but a key factor is the existence of different tech platforms across various departments. Use of disparate tools for different functions can lead to decentralised management of data. For instance, while the sales team might know how many units of a product a customer has purchased, they may have no visibility into how quickly the customer pays their invoices or how many interactions they’ve had with marketing and communication collateral before making a purchase.
There are other data issues that businesses face too. Among them is poor data quality. This can be caused by manual data collection practices that often yield inaccuracies, inconsistencies, and redundancies. Poor data quality forces businesses to spend a lot of time and resources on cleaning up, which further prolongs the analysis process. The best approach to solve these issues is to digitalise and unify data sources with the right tech platform that interconnects all departments.
The right software matters
Fortunately, with the right software, achieving a unified view of data becomes much simpler. Effective data analytics software will bring disparate data points together and make analysis easier. To do this effectively, the software should provide native integrations with a diverse array of data sources, including local files, feeds, databases, and business applications.
Beyond that kind of integration and unified view, what should organisations look for in business analytics software?
First, it should be accessible to all users—whether they are business users, data analysts, data engineers, or BI specialists—ensuring ease of use and value for everyone. The software should also offer pipeline builders, be compatible with other forms of software, support streaming analytics, deliver real-time insights, and provide unified metrics.
In addition,the software must evolve with a business’ changing data analytics needs. This means supporting features like generative AI analytics, predictive AI, and machine learning capabilities. The ability to trigger actions based on alerts and pipelines, connect to niche business apps, and integrate multiple BI and data analytics tools will further enhance its benefits.
Ultimately, the software should demonstrate clear value by reducing manual effort and streamlining processes, handling large datasets efficiently, and delivering cost and time savings.
The data’s there; now bring it together
Given the clear benefits that good data analytics software offers businesses, embracing it should be a no-brainer. Most organisations already sit on a treasure trove of data; it’s simply not being put to effective use. A unified data analytics software can change that by bringing together disparate data points and providing a consolidated view with actionable insights. Implemented correctly, those insights can supercharge a business’s growth trajectory.
