WHY IT MATTERS: Digital Transformation

The 2022 edition of the Critical Capabilities for Analytics and Business Intelligence Platforms has the same 12 capabilities as the 2021 edition. However, the underlying questionnaire used to evaluate all 20 vendors was expanded, adding nine new subcriteria for a total of 79 questions.

This frequently-updated page contains real-life examples and diagrams from Upsolver customers who are using AWS data lakes. While the Upsolver platform itself is a key component in all of these architectures, we hope even non-customers can learn from these examples when it comes to the use cases, considerations, and design patterns that go into a typical cloud data lake.

Data cleaning is a massive part of data pre-processing and model building for machine learning algorithms so it's something you can never miss.

Looking for a data visualisation tool or SEO report templates? Grab these FREE Data Studio Templates to speed up your reporting (and more).

Expert data scientists and other professionals working in data science roles require capabilities to source data, build models and operationalize machine learning insights. Significant vendor growth, product development and myriad competing visions reflect a healthy market that is maturing rapidly.

In this report, TDWI uncovers deeper insights that give users new perspectives on business questions. AI will transform BI and the way people make decisions and act. Rather than start with a hypothesis, data analysts will begin with an AI-driven insight. Instead of querying data to prove or disprove their hypothesis, users will query data to expand or validate a machine-generated insight or recommendation—or they might act on the AI-based insight at face value. But to get to that point, AI-infused BI tools will need to gain people's trust by consistently delivering accurate, relevant, and transparent insights within the context of a business user’s existing workflow.
In the future, AI-infused BI tools will go beyond just surfacing insights; they will recommend ways to address or fix issues, run simulations to optimize processes, create new performance targets based on forecasts, and take action automatically. And yes, machines will make some decisions for us—especially operational decisions in real-time environments. We see this today with fraud detection and online trading systems, but it will become more pervasive.

More than 1,300 people mainly working in the tech, finance and healthcare revealed which machine-learning technologies they use at their firms, in a new O'Reilly survey.

Gartner has recognized ThoughtSpot as a Leader in the 2019 Magic Quadrant for Analytics and BI Platforms. ThoughtSpot’s search and AI-driven analytics platform makes it easy for anyone to get insights in seconds.

Lors de la soirée du Débat des chefs, bien des choses ont été dites sur Internet, par les électeurs qui suivaient le débat, par les analystes, les sympathisants et même, les partis eux-mêmes. Voici une analyse de ces propos produites par les gens de Semeon Analytics pour chacun des chefs présent lors du débat de jeudi…

This post explains why traditional marketing analytics tools can't deliver the results CMO’s demand and what you can do to overcome their limitations.

Use Redash to connect to any data source (Redshift, BigQuery, MySQL, PostgreSQL, MongoDB and many others), query, visualize and share your data to make your company data driven.

Now a new breed of software applications is reshaping sales force management. Their common characteristic: Using digital data exhaust, which is the data generated from the regular activities of a sales force or their customers, to change the behaviour of frontline sales representatives in ways that dramatically improve sales productivity and effectiveness.

Onfido delivers next-generation background checks, helping the world’s most innovative businesses verify anyone, anywhere.