How to Solve a $65 Million Data Problem

Maximize ROI of your data with Altair Knowledge Hub

If you’re sitting on a big pile of data and thinking you’re ahead in the data-driven game, you could be in for a big surprise.

For data to be considered high-quality, it must be readily available, easily found, and usable by all your employees.

The biggest data problem for most companies isn’t the accumulation and storage of as much data as possible, but its accessibility.

Simply put, data accessibility refers to the ability to store, retrieve, and act on data housed in a database or other repositories such as spreadsheets, PDF reports, and websites.

In the past, enterprises didn’t pay enough attention to gaining full accessibility to the data they had collected.

And it’s costing them dearly.

A recent Forrester research has found that just a 10% increase in data accessibility can result in more than $65 million additional net income for a typical Fortune 1000 company.

Even more surprising is that although we’re very good at collecting information, 87% of data workers consider data to be their organizations’ most underutilized asset.

To solve your data quality and accessibility problem, we need to first understand the root cause.

Employees don’t trust the data

Another Forrester survey discovered that managing data quality is the biggest issue for most organizations. Transposing, collating, and manipulating data manually on spreadsheets means that results are error-prone. In fact, a whopping 88% of spreadsheet documents contain errors.

It’s not surprising that most people believe they have poor quality or inconsistent data, which they can’t fully trust.

If your employees don’t believe that the data is accurate, it’s much harder for them to take action on it.

The data is not usable

A lot of data is locked in sources such as PDF reports and websites that can’t be easily transferred into Excel for further cleaning, manipulation, and analysis.

In fact, data analysts spend up to 80% of their time in preparing data instead of analyzing it to extract valuable insights.

In addition, they have to manually go through the same extraction, cleaning, and manipulation process whenever there’s an update on the data (from third-party websites, for instance). Not only is it labor-intensive and time-consuming but it’s also prone to delays and errors.

Data not shared efficiently

After hours of hard work in preparing and analyzing the data, most Excel spreadsheets end up collecting dust in an analyst’s hard drive.

Not the best way to get the highest ROI from your data, don’t you think?

For the data to be usable, it needs to be shared across the organization so that everyone involved can get access from anywhere at anytime.

However, just storing your Excel files on any cloud storage can cause problems too.

Sensitive data needs to be protected by governance features so they don’t compromise the security of the information.

An easy solution to your $65 million data problem

To make your data accessible and useful, you need a self-service data preparation software that offers an efficient and error-proof way to extract and prepare data from a variety of sources with just a few clicks.  At the same time, this agility needs to be balanced with governance and controls to ensure data access is restricted to only the right set of people when necessary – and data that people are using is curated and blessed.

Knowledge Hub is our new data preparation platform designed to help you get the most out of your data – whether it’s data another person in the organization is creating, or data that’s locked away in a report or a database – and share the analytics efficiently across the entire organization. It also allows IT to control this data access and collaboration so governance is properly enforced.

Knowledge Hub is a browser-based platform offering team-driven data preparation and a centralized data marketplace to speed collaboration and drive governance across the enterprise. It includes:

Data preparation for the masses
Data marketplace housing secure, governed and blessed data
Data socialization for reuse of models and curated data
Controlled collaboration reduces governance burden on IT without compromising data integrity
Gamification and visibility to encourage participation and contribution