Smart Data Collective

MAY 8, 2022

Big data, analytics, and AI all have a relationship with each other. For example, big data analytics leverages AI for enhanced data analysis. In contrast, AI needs a large amount of data to improve the decision-making process. Consumers are presented with ads every day they access the online world.

Data Mining 267

Data Mining Data Analysis Analysis Finance 267

Datapine Blog

SEPTEMBER 27, 2022

Recently published in 2021, “SQL for Data Scientists” by author and experienced data scientist, Rénee Teate, teaches its readers all the skills that data scientists use the most in their daily work. This SQL beginners book takes a fun approach to show the fundamentals of SQL and how to really take advantage of the language.

Data Analysis 117

Data Analysis Knowledge Analysis Business Intelligence 117

CIO

JANUARY 20, 2023

Trusted and governed data: Modern BI platforms can combine internal databases with external data sources into a single data warehouse, allowing departments across an organization to access the same data at one time.

Business Intelligence 900

Business Intelligence Intelligence Intelligence Business 900

Datapine Blog

MAY 14, 2019

Zettabytes of data are floating around in our digital universe, just waiting to be analyzed and explored, according to AnalyticsWeek. By gaining the ability to understand, quantify, and leverage the power of online data analysis to your advantage, you will gain a wealth of invaluable insights that will help your business flourish.

Algorithm 140

Algorithm Data Analysis Knowledge Analysis 140

CIO

DECEMBER 22, 2022

“For example, this style makes it more feasible for data scientists to have the support of software engineering to provide what is needed when models are handed over to operations during deployment,” Ted Dunning and Ellen Friedman write in their book, Machine Learning Logistics.

Data Mining 805

Data Mining Data Analysis Learning Management 805

Elegant BI

JANUARY 31, 2019

A comprehensive, self-serve advanced analytics solution Incorporates computational linguistics, analytical algorithms and data mining into a self-serve environment and provides an easy-to-use NLP search capability for swift, accurate data analysis.

Business Intelligence 52

Business Intelligence Intelligence Intelligence Predictive Analytics 52

Datapine Blog

MARCH 31, 2022

This all-encompassing branch of online data analysis is a particularly interesting field because its roots are firmly planted in two separate areas: business strategy and computer science. Data Analysis : Most BI skills and intelligence analyst-related skills are about using data to make better decisions.

Business Intelligence 95

Business Intelligence Intelligence Intelligence Business 95

Datapine Blog

OCTOBER 25, 2022

Understanding where and how to leverage huge amounts of information, how to integrate analytics processes into everyday operations, and how the use of data no longer needs to be a technical task for the IT department only, among other useful knowledge. 3) “The Data Detective: Ten Easy Rules to Make Sense of Statistics” by Tim Harford.

Business Intelligence 117

Business Intelligence Intelligence Intelligence Business 117

Datapine Blog

AUGUST 29, 2022

Companies, both big and small, are seeking the finest ways to leverage their data into a competitive advantage. With that in mind, we have prepared a list of the top 19 definitive data analytics and big data books, along with magazines and authentic readers’ reviews upvoted by the Goodreads community. trillion each year.

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Data Mining Predictive Analytics Startups Data Analysis 105

Datapine Blog

MARCH 25, 2022

Predictive analytics : This method uses advanced statistical techniques coming from data mining and machine learning technologies to analyze current and historical data and generate accurate predictions. The advantages are clear, but what about the indispensable features a simple visual overview can provide you with?

Business Intelligence 105

Business Intelligence Intelligence Intelligence Business 105

Alpha Sense BI

DECEMBER 13, 2022

One major reason behind this gap is that the sheer volume of data companies can now access has made manual market analysis impossible. Modern enterprises need market analysis tools to enable critical ca pabi lities such as AI-supported s ear ch and data mining, data visualizations, a uto mated aler ts, and larger trend analysis.

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Analysis Marketing Marketing Primary Research 97

Smart Data Collective

OCTOBER 25, 2023

Well, it is – to the ones that are 100% familiar with it – and it involves the use of various data sources, including internal data from company databases, as well as external data, to generate insights, identify trends, and support strategic planning. In the 1990s, OLAP tools allowed multidimensional data analysis.

Business Intelligence 241

Business Intelligence Data Analysis Analysis Data Mining 241

Elegant BI

OCTOBER 3, 2018

You don’t have the time, the budget or the inclination to make every business user a data scientist. The Advantages of Advanced Analytics are well known. Is Augmented Analytics Easy Enough for the Average Business User? Augmented Analytics benefits a business, its users and its customers, partners and stakeholders.

Data Mining 52

Data Mining Algorithm Advantage Advantage 52

Elegant BI

DECEMBER 12, 2018

Many businesses are just discovering the benefits of self-serve business intelligence and establishing data democratization initiatives but, as every business manager and team member knows, business markets and competition move rapidly and yesterday’s business intelligence initiatives are morphing into advanced analytics efforts.

Data Mining 52

Data Mining Algorithm Advantage Advantage 52

Elegant BI

JANUARY 25, 2018

Clickless Analytics incorporates NLP within a suite of Augmented Analytics features, leveraging computational linguistics, data mining, and analytical algorithms to provide a self-serve, natural language approach to data analysis.

Analysis 52

Analysis Data Mining IT Business Intelligence 52

Datapine Blog

NOVEMBER 27, 2019

Today, most companies understand the impact of data quality on analysis and further decision-making processes and hence choose to implement a data quality management (DQM) policy, department, or techniques. According to Gartner, poor data quality is estimated to cost organizations an average of $15 million per year in losses.

Business Intelligence 144

Business Intelligence Intelligence Intelligence Business 144