Organisations have more data than ever at their fingertips. In order for it to be valuable, it needs to be tracked, managed, cleaned, secured and enriched throughout its data journey to provide the most successful results for your organisation. Intelligence from big data can:
- detect issues and solve them
- provide insight into your customer lifecycle
- inform ways to increase sales
Big data also comes with big data challenges, with three common issues that businesses struggle with:
- Lack of data
- Incomplete data
- Limited or no access to data
These issues are usually experienced when there is insufficient planning around how organisational data is managed and accessed by the organisation as a whole; your data strategy. These issues may not completely stop your AI initiatives but they can have a negative impact on them.
Your data should be useful and reliable across your organisation. Given that data health is a measure of your data’s value, its transparency and accessibility are as important as its quality. To ensure that your organisation’s data is healthy, you must be able to prove that it is valid, complete, and of sufficient quality to produce analytics that decision-makers can feel comfortable relying on for business decisions.
To ensure that your data is healthy, it is recommended that you utilise a data management health check; a data platform which incorporates both data integration and governance capabilities. This will provide both a reading on the health of your data and how to cure unhealthy data, with insight into the data you can trust and the tools you should utilise to correct the data that you can’t.
The big data challenges that you will face in your organisation will depend upon your industry, infrastructure and the types of data you are managing. Here are five signs that your organisation needs a data management health check.
Sign One: You are gathering outdated/inaccurate data
If you are gathering data from a variety of sources and in a range of formats, you can face problems when it comes to data analysis and the extraction of insights from it. Additionally, if you have too much data in your database, it is very likely that you have collected inaccurate and/or invalid data. This issue usually begins at the data gathering stage of your data lifecycle and occurs more often when the data is collected from different applications that don’t always talk to each other. This, along with the data being analysed without data quality, validity and security safeguards in place and by various employees that do not have access to the full picture, it usually results in low standards of quality and accuracy. If you can’t trust your data, you therefore cannot trust the analysis that is derived from it. This is classed as poor data collection.
Sign Two: You cannot locate the data that you require
Big data analytics is ‘big’ and, with the vast amount of data available, it can be difficult to establish what is of value to your organisation and what isn’t. There is data readily available for, for example, website visitors, financial data, conversion rates, churn rates and more. Whilst much of this data will be useful, there will be large parts of it that are not relevant to your organisation. If the data that is coming in your business is unfiltered, unstructured and via multiple channels, this issue will typically occur.
"Onward Homes have recently had a data health check and found the process really helpful. Very professional report has allowed us develop an action plan to make the best use of our current technology, alongside thinking about our future requirements."
Anita Wright, Head of Data and Insights - Onward Homes
Sign Three: Your data is stored in separate databases that don’t talk to one another
If your data is stored in silos, this means that your employees are not looking at the same data; they are accessing limited parts of data that do not provide insights into the full picture of what is occurring. Without a 360 perspective of your data, it is unlikely that you will be able to formulate reports that are accurate, reliable and valuable.
Sign Four: Disregarded data security and protection
Significant increases in the amount of data you are collecting results in a higher likeliness of security breaches. If your data is unorganised, this risk is greater. As your organisation grows, there is an increased likeliness that security lapses will occur due to the addition of new tools to your software stacks and incorporating new technologies for data analysis. Potential threats to data security include:
Data sources that are not secure: Gathering data from these channels results in systems that are increasingly vulnerable to malware and unintentional external data leakages.
Stored data that is unsecure: Storing data with no safeguards in place is vulnerable to problems such as data harvesting, malware and data leaks. Without access control, encryption and firewalls, your organisation is vulnerable, as well as the privacy of your customer’s data.
Gathering invalid data: If you are collecting data from a variety of uncontrolled sources, there is a probability that you are gathering invalid and potentially damaging data, which will have a negative impact upon the analysis that is generated from it.
Not adhering to privacy laws: There is a high risk of data exposure if you do not have a strategy in place to ensure compliance with data protection laws. If you do not track your data collection and ensure it is consistent, you will not be able to ensure that your users are giving their consent.
Sign Five: Not enough big data professionals
Finding qualified big data professionals who can organise, manage and analyse your data is a real challenge given the shortage in this area. It is therefore much more challenging for organisations to gather, manage and compile actionable reports from big data as their team does not have the knowledge to operate the technology at an expert level, by qualified people.
Are you experiencing one or more of these challenges? If so, you could significantly benefit from a data management health check, which provides:
- a reading on the health of your data
- how to cure unhealthy data
A data health check will provide you with insight into the data you can trust and the tools you should utilise to correct the data that you can’t. The Enterprise Data Management Health Check provided by Catalyst BI, combines both technologies and behaviours to measure and manage data and processes for better discovery, transparency and value. It scores your data management on the following key pillars:
- Data Sourcing and Quality
- Data Integration
- Data Warehouse
- Data Governance
The health check reviews the condition of your company's data and how well it supports effective, timely decisions and business objectives. It ensures that your data, technologies, processes and governance are fit for purpose.
From wanting to prove your current data landscape requires investment to propel your organisations data to the next level, to just being unsure which technologies are required to solve your data management challenges, the EDM Health Check ensures that you are leveraging the best technologies available. And with a comprehensive data strategy that clearly outlines who handles your data, where it is sourced from, where it goes to and how it moves through your systems, you will be able to develop actionable insights and create positive organisational change.
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