As any data analyst knows, when it comes to data management, preparing the data for analysis is more than half the battle (roughly 61% of it according to a recent TDWI Pulse Report). Without the right preparation it’s going to be of limited use when it comes to analysis and informing critical business decisions. That same Pulse Report found 83% of companies can only use 25% or less of their data.  And as the first piece of an organization’s data fabric (as discussed in a previous post), data prep sets the standard for the remainder of your data management processes.

Within most organizations, data prep begins with pulling in data from any number of sources (CRM, social, email) in any number of formats (.pdf, .dbf, .csv, .xls), not to mention any data that’s scanned and processed via OCR. With all these sources and formats your data fabric can very quickly start to look less like a single sheet and more like a patchwork quilt (not ideal).

To ensure a seamless data fabric that gets your organization off to a strong start, ensure your data preparation solution includes the processes and functionalities required for success.

Prep Process Requirements

Processes are just as important as the tools that implement them, make sure your prep (and pre-prep) processes include:

• Understand Business Goals - This assures the data being used is aligned with measurable and achievable performance indicators, that are mapped back onto the data and analytics to be used.

• Data Access – Make certain your tech solution allows you to access data from any source – no matter the origin, format or narrative. Why does this matter? Increased access to data means less manual work, faster insights and more "aha" moments for your organization. But data access problems can cause major roadblocks for organizations

• Clean Data and Improved Data Quality - Studies show that manual data prep is not only error-prone, but time-consuming and costly. Business decisions rely on analytics, you can’t afford mistakes. And if the data is inaccurate or incomplete, your analytics could inform wrong business decisions.

• Blend and Reconcile Data - Clean data is the foundation of analytics, but single datasets do not tell a complete story. Your marketing team alone probably has at least six systems they are trying to reconcile data from. Trying to blend data at this scale in Excel requires advanced knowledge of macros, functions and/or VLOOKUPS. Plus, it’s not very repeatable. Leveraging automation to blend data is a game-changer for saving time, effort, and errors.

• Transform and Instantly Re-Format Data - Being able to quickly change the way data is summarized and presented enables business analysts and executives to quickly consider different slices and views of data.

• Export and Use Your Data - Now that your data is all cleaned up, blended and enriched for analytics, you need to send it somewhere.  You’ve probably invested in specific visualization and reporting tools and your organization probably has preferred data reporting formats. Being able to export to any common platform makes it easy to maximize investments you’ve made in other BI tools and drive insight through your entire organization.

• Expanded Connectivity - Every company has a unique technology stack. Enabling you to be flexible with your data connections further simplifies your ability to create valuable analytics, based on all of your organization’s data.

• Make Tasks Instantly Repeatable - This is quite possibly the most important step of prep (and an enormous time-saver). Many analysts need to generate the same reports from the same systems on a monthly or quarterly basis. Without the right tech to support it, that often means performing the same data preparation steps, exporting the finalized reports to the same format, and sending them to the same group of people (over and over and over). Automation stops the cycle, so that rather than spending time tediously re-formatting data and repeatedly generating reports, analysts are free to explore their data and find brand new insights to create value for their organization

Allow Access for All

If data is prepped in the IT department and no one in marketing ever sees it, does it make a sound? Data affects and informs every part of your business, so every part of your business should be able to easily access that data from the start.  Make sure your data prep solution allows for easy, secure collaboration across the organization so no one is in the dark when it comes to data-driven decision making (without sacrificing strict adherence to security, lineage, and governance requirements).

Note: Access for all won’t necessarily mean the same access for all. Make sure your team members have appropriate permissions based on their data needs to avoid any mishaps.

Keep Things Quick and Easy

As the speed of business accelerates expectations for the pace of data-driven decisions have picked up speed too. That’s one of the key reasons the days of asking IT to build you a report are all but dead and self-service data prep tools are the new normal. However, all self-service is not created equal. Unless your organization is entirely data science-focused, you’ll want a system that is useful with zero coding. Not only is coding time-consuming, it’s likely to minimize the usefulness of the tool for a lot of your organization. Data prep with no code requirements will ensure that teams throughout your organization can access and collaborate on data prep, analysis, and beyond.

Piecing together the strongest data fabric for your organization can get complicated quickly. But keeping things seamless is critical to the success of your data management and your business. Whether you’re just getting started with the first stitch or already working with a patchwork quilt situation, Altair can help strengthen your data fabric from start to finish. Contact us here to get started.