Remove Data Architecture Remove Data Quality Remove Data Strategy Remove Unstructured Data
article thumbnail

Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

article thumbnail

What is a data engineer? An analytics role in high demand

CIO Business Intelligence

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 131
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

How Data Management and Big Data Analytics Speed Up Business Growth

BizAcuity

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

article thumbnail

Decades of empowering efficient data decisions

IBM Big Data Hub

As a company, we have been entrusted with organizing data on a national scale, made revolutionary progress in data storing technology and have exponentially advanced trustworthy AI using aggregated structured and unstructured data from both internal and external sources. .

article thumbnail

Data democratization: How data architecture can drive business decisions and AI initiatives

IBM Big Data Hub

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. This includes tools that do not require advanced technical skill or deep understanding of data analytics to use.