Tag: Networked BI

Four areas retailers must analyze to stay ahead of the competition

Aug 27, 2019 Mona Patel

Have you used a digital product or service while shopping in the past year? The answer is almost certainly “yes” and each time you are online, your actions generate data – from research, online ordering or in-store pickup, coupons, mobile payments, voice commands and more. The question is, how do retailers make the best use of this data to stay ahead of the competition?

Read More

Birst 7: A new level of ease of use and collaboration across centralized and decentralized analytic teams

May 14, 2019 Mona Patel

Cloud, digital transformation, mergers and acquisitions, big data analytics, data monetization, and more are all critical business initiatives creating an even greater divide between centralized IT and decentralized analytic teams in the business. This is why it is all too common for an organization to utilize at least two different Business Intelligence (BI) tools to support these different analytic needs.

Read More

Birst Smart Analytics: Using AI to Operationalize BI

Jan 29, 2019 Mona Patel

How do you deliver more insights out to more people? Operationalizing BI and analytics – that is, putting the power of data in the hands of everyone across the enterprise, not just analysts and data scientists – has always been the mantra for Birst co-founder Brad Peters.

Read More

How AI is Lowering the Barrier to Entry for BI and Analytics

Dec 18, 2018 Mona Patel

According to Gartner, more than 3,000 CIOs ranked Business Intelligence (BI) and Analytics as the top differentiating technology for their organizations. If BI and Analytics is such a game-changer, then why is the average adoption rate in organizations only 32%? Despite the efforts of Cloud BI vendors making it easier for users to acquire, explore, and analyze data sources without IT dependency, lack of data literacy and analytic skills still hinder widespread adoption for data-driven decision making.  But the industry is undergoing a fundamental transformation. The mainstream arrival of Artificial Intelligence (AI) brings with it the potential to finally meet the demand for actionable, enterprise-wide, fact-based decision making.

Read More

How “Able” Is Your ETL Process? 8 Ways To Modernize Data Prep, Part 2

Nov 14, 2018 Richard Reynolds

In Part 1 of this blog, I gave a high-level comparison of traditional extract, transfer and load (ETL) tools, desktop data preparation tools and Birst’s modern, built-for-the-cloud ETL tools for data analytics. In this blog, I’ll dive deeper into the eight key ways that, of the three options, Birst is best “able” to meet the rigorous requirements of today’s enterprise users.

Read More

How Are You Analyzing and Adjusting to the Mobile Shopper?

Oct 11, 2018 Mona Patel

Every retailer is facing a similar challenge. If you are a retailer and constantly feel the pinch from online giants like Amazon and Google, you have an opportunity to gain back control and competitive advantage with more personalized products and services, building that intimate relationship that these giants simply cannot provide.

Read More

How “Able” Is Your ETL Process? Modernizing Data Prep, Part 1

Oct 9, 2018 Richard Reynolds

For all the exciting discovery that data analytics enables, data preparation involves, for most users, an equal amount of drudgery. That’s true for a number of reasons, first and foremost being that enterprise data is rarely structured for analytic use; it’s often designed for transactional system performance or to minimize storage. Wrangling in data that’s spread across different locations and technologies (database, cube, cloud-based, on-premises, flat files, etc.), and then cleaning up “dirty” (incorrect, improperly encoded, duplicated or blank) data is a time-consuming and labor-intensive task, constantly repeated as data sources come and go.

Read More

Improve your company’s bottom line with analytics

Mar 22, 2018 Richard Reynolds

The explosion of data in the financial services industry is creating new opportunities for business intelligence and analytics. At the same time, this explosion presents significant challenges. Over 2.7 zettabytes of data exist in the digital universe today. Every day, financial services companies seek to use these massive volumes of data to increase margins, reduce risk, boost customer satisfaction, and win in a globally competitive marketplace.

Read More