According to Forbes, 95% of businesses lack the expertise or budget to adequately deal with their large amounts of unstructured data. This means their data continues to grow unabated without any major QA on their quality, without being structured into an easily consumable data warehouse, without being analyzed for trends, without being turned into insightful visualizations, and without being used in predictive AI or Machine Learning applications. In short, many companies are leaving one of their most profitable business assets untapped.

Unfortunately, a lack of expertise is only one of the twelve common data science problems facing corporations today. In this blog, we break down each of the twelve in more detail.

The 12 Data Problems Companies Face

Siloed Data

Siloed Data is data held by one group or business unit that isn’t shared by others. A very common example of this is between your marketing and sales groups; your sales might be running Dynamics CRM or Salesforce, yet your marketing team might be running Marketo or HubSpot. While the data in these tools can connect, often a lack of overarching data management and clear communication means they don’t.

Data Entry Errors

Data entry errors are quality problems caused at the point of entry. Data entry problems can be due to transcription or transposition errors and are often caused by human input. Unfortunately, getting quality output is only possible when there’s good data input.

Poor Data Quality

One large issue with data is data quality. How many times have marketers pulled a list of emails out of their CRM, only to find that many of the email addresses bounced? Or how many times have corporate sales people tried connecting with leads who were no longer at their former companies because CRM data was outdated?

Data quality is comprised of dimensions: timeliness, integrity, conformity, uniqueness, consistency, completeness, and accuracy. Any one of these dimensions gone wrong can effect the accuracy of data analysis, visualization, and ultimately its usability for predictive analytics or machine learning.

At Aptude, our data engineering team specializes in creating and implementing best practices for data quality for this very reason: if you have data but it’s not good, you might as well not have the data at all.

Data Deluge

Many organizations have found ways to collect massive amounts of data. Unfortunately, the ability to collect data far surpasses most organization’s ability to process, manage, and analyze the data. Too much data, especially unstructured data, results in data lakes that take up space without positively contributing to your company’s bottom line in any way. To make matters worse, the longer data sits without management, the less valuable it becomes.

To make better use of your data, we recommend creating a data warehouse which can be used in dashboards and on-demand visualizations. Once that infrastructure is in place, your data will begin to become more of an investment rather than a cost because stakeholders can make increasingly data-driven decisions.

Lack of Data Expertise

Having a team which can’t implement data engineering, predictive analytics, machine learning, or big data solutions is a problem if you want to stay competitive. Your “digital native” competitors often have a data-driven organizational culture out the gate, and can very quickly overtake legacy corporations who can’t respond to trends as quickly.

If you can’t hire whole teams in-house, we recommend chipping away at your data projects through clearly defined projects. You’ll be able to rotate in team members with various skillsets throughout the life of the project, allowing you to control costs while still getting highly valuable work done.

Data Duplication

Data Duplication happens when you have excessive copies of data in multiple places. This in turn reduces your storage capacity without adding extra value. To solve this problem, organizations must develop a “Single Source of Truth” for data, which is often the value of creating data pipelines which feed into data warehouses.

Lack of Data Consistency

Another problem companies face? A lack of consistency in the measurement of variables throughout the datasets. This misalignment means that data can’t easily be combined into a single, structured location without a lot of cleanup work.

To fix this problem, companies can start the conversation by developing data dictionaries. A data dictionary, done right, will list the data types, fields, dimensions, and metrics in a system. Once you know the quality and standard of your data, you’ll be able to evaluate the extent of the differences between your systems and then come up with an action plan to solve the inconsistencies.

Cross-Team Misalignment

One thing we’ve seen over and over again is cross-team misalignment, especially among data teams. For example, we see many cases where the Data Engineering team has different procedures, goals, and standards for data management than the Data Visualization team does. This misalignment creates a push-pull situation where one team undoes the work of the other, creating resentment and chaos along the way.

Aptude’s Technical Project Managers are adept at coming into an organization and facilitating communication and shared practices between data teams. This results in more alignment between team members and more consistent work across departments.

Lack of Visualization

Another common data problem is a lack of visualization of data. When this happens, there’s no way to tell data-driven stories or glean fast insights from your data. So you’re collecting tons of data, but not able to make good use of it.

At Aptude, we have decades of experience creating robust data visualizations and dashboards (such as in Power BI) for our clients. We’ve created dashboards for CCRPI performance, K12 smart reporting systems, for transportation, and for portfolio and project management – just to name a few. Learn more about our data dashboarding capabilities and case studies.

Privacy Concerns

A growing problem for corporations, especially global corporations or those dealing with PPI, is data privacy and security. This problem occurs when data stored isn’t secure or compliant with privacy laws and regulations, or has lax security measures.

Lack of Data Transparency

A lack of data transparency is an inability to easily access and work with data no matter their location or application source and to trust that data’s accuracy and consistency. According to one 2017 study, “32 percent of marketers named ‘a lack of transparency’ as the biggest factor inhibiting the future growth and scale of programmatic marketing.”1

In another study by Forrester – this time of executives, the researchers found that, “of the 100 executives polled, 85% complain of lack of visibility into data to define target audiences. And almost as many say there is no ranking for quality and authenticity.”2

To add transparency and trustworthiness to your data, corporations should consider adding third-party data pipelines to their existing data sets to augment missing data and serve as quality control.

Improper Data Linking

Finally, the last data problem seen often in corporations is the lack of an ability to connect different data sets together to perform semantic queries. Or if data is linked together, that data is improperly linked and thus less valid for decision-making.

Aptude can help.

When you’re ready to figure out where to start and what you need in terms of data, manpower, tools, and budget, then we can help. Many of our projects involve data-related initiatives, especially since we now have a Python Center of Excellence in Mexico City, Mexico. Getting our help is as easy as contacting us via email, form, or phone, and starting a conversations is absolutely obligation-free. We even send an NDA to protect your confidential information. Contact us today.

Keep Moving Forward with Aptude

Aptude is your own personal IT professional services firm. We provide our clients with first class resources in a continuous, cost-containment fashion.

Our support services will free up your senior IT staff from the overwhelming burden of day-to-day maintenance issues. Now they’ll have time to launch those new projects and applications you’ve been waiting for. Simply put, we can free up your resources and contain your costs. Let’s have a quick chat to discuss our exclusive services.

CONTACT US TODAY
Source:
1. https://www.prnewswire.com/news-releases/survey-marketers-say-lack-of-data-transparency-stunts-programmatic-growth-300448210.html
2. https://www.mediapost.com/publications/article/310141/the-data-swamp-forrester-study-shows-lack-of-tran.html