The Best Data Prep Approaches for Newbies

How to Democratize Analytics for Better Return on Your Data

Mike OrtmannJanuary 29, 2020

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When a new hire joins a business, they are eager to make an impact and prove their worth. Data-centric businesses that utilize enterprise-level analytics and business intelligence to drive operations, innovation and revenue give employees confidence in their ability to succeed, because they know they’ll have ready access to the information they need to make faster, better business decisions. This type of corporate culture offers both new and existing employees the ability to access and prepare high quality data in order to drive insights that give organizations a competitive edge.

Critical Features of a Data-Driven Culture

Today’s data-driven organizations put data at the center of the enterprise and prioritize it as a vital organizational asset. They use data analytics to track business trends, improve operations, gauge the competition and develop customer insights. However, building a data-centric organization depends on equipping users with critical data governance capabilities such as the knowledge and tools to understand data, policies and processes to prepare reports, analyze critical data and leverage those results to make better business decisions.

It is imperative that organizations have the right technologies to facilitate effective data prep and analytics and enable users’ self-service access to the data they need. Top companies rely on their data to make educated and strategic business decisions, but it’s often difficult for business users to accurately analyze information if data is housed in different, disparate silos. A siloed approach is a barrier to meaningful insights, as locating, accessing and aggregating information can be a time-consuming and complex process.

When business users do not have self-service access to the data they need to answer complex analytics questions, they must depend on IT. But IT resources are often overburdened with competing responsibilities and shifting priorities, relegating business user requests to the back burner. Without timely analysis, business leaders lose opportunities and critical business intelligence needed for operational decision-making.

To overcome the challenges of siloed data and slow analysis, companies require agile, business user-oriented technologies that empower business users, expedite data prep and enable speed to insights.

Modern Data Prep Capabilities to Drive Analytics and Business Intelligence

Today, technologies exist that are specifically built to facilitate data preparation and analysis by business users, without the added time and expense involved when they must rely on technical staff to provide it for them. They are constructed from the ground up and allow users to rapidly analyze structured, semi-structured and unstructured data for better analytics and business intelligence. Characteristics often include:

  • Flexible Data Flow: Modern data prep tools do not require overarching data models or schemas, allowing analysts to immediately build out analytics without waiting on all possible requirements. Not only does this eliminate the overhead costs and effort that the rigid structure of relational database tools requires, but it makes it easier to unify disparate data sources.
  • Data Quality: New technologies ensure high integrity, accurate data, giving business users increased confidence in their business decisions. Users are empowered to take on large data sets and decipher complex analytics.
  • Rapid Prototyping: Business users want to consider new data sources, interpret data in a more streamlined fashion, explore data more completely, evaluate new hypotheses, and make ad-hoc discoveries. New tools offer a flexible data model to enable business users to compile data and quickly build analytics, with no programming required.
  • Simple Query Interfaces: Visual models increase process consistency by visually documenting the step-by-step processes. In addition, they can help automate analytics processes and enable immediate changes.
  • Enhanced Business Results: Predictive analytics capabilities empower organizations to confidently predict what will happen next and enables better decision making for improved business outcomes.
  • Simple Data Management: Data analysis requires effective data management, meaning the right architecture, policies, practices and procedures are required to support real-time analytics.
  • Competitive Edge: Organizations that prioritize agile, self-service analytics have the ability to quickly identify new revenue opportunities and increase efficiencies across the enterprise.

Modern data-centric tools deliver the speed, reliability, flexibility and control required to empower business users to identify patterns, anticipate future events, allow true predictive analysis, and ultimately, thrive as a data-driven employee.

Are you looking for additional information about data prep? Check out the white paper below.

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