Apiumhub

MARCH 16, 2021

With more and more data available, it’s getting more difficult to focus on the information we really need and present it in an actionable way and that’s what business intelligence is all about. In this article we will talk about Business Intelligence tools, benefits & use cases. . What is Business Intelligence.

Business Intelligence 117

Business Intelligence Tools Artificial Inteligence Technical Review 117

Datavail

OCTOBER 18, 2022

You can’t have superior “Business Intelligence” (BI) without excellent data retrieval, organization, and management. Data Discovery = Key to BI. Despite BI being the popular buzzword these days, too many companies fail to invest in the data discovery pipelines needed to generate that analytical data.

Business Intelligence 52

Business Intelligence Data Architecture Storage 52

TechCrunch

JUNE 1, 2022

We’ve long documented the challenges that DevOps and operations teams in specific areas like security face these days when it comes to data observability: a wide range of services across the landscape of an organization’s network translates into many streams of data that they need to track for performance, security and other reasons.

Analytics 246

Analytics DevOps Storage Business Intelligence 246

InfoWorld

FEBRUARY 9, 2024

Microsoft Fabric is an end-to-end, software-as-a-service (SaaS) platform for data analytics. It is built around a data lake called OneLake, and brings together new and existing components from Microsoft Power BI, Azure Synapse, and Azure Data Factory into a single integrated environment.

Big Data 81

Big Data Azure Google Cloud Data 81

Perficient

MARCH 19, 2024

If you have built or are building a Data Lake on the Google Cloud Platform (GCP) and BigQuery you already know that BigQuery is a fully managed enterprise data warehouse that helps you manage and analyze your data with built-in features like machine learning, geospatial analysis, and business intelligence.

Data 111

Data Google Cloud Analytics Serverless 111

The Crazy Programmer

MAY 12, 2021

Companies everywhere are handling more data than ever and all these terabytes of data need to be stored somewhere. Should you store the data in a database, a data warehouse, or a data lake? Choosing the right data storage solution will depend greatly on how the data is going to be used.

Data 162

Data Healthcare IoT Pharmaceuticals 162

Datavail

APRIL 12, 2021

MariaDB is a flexible, modern relational database that’s open source and is capable of turning data into structured information. It supports many types of workloads in a single database platform and offers pluggable storage architecture for flexibility and optimization purposes. MariaDB’s default storage engine is InnoDB.

Storage 98

Storage Engineering Open Source Business Intelligence 98

Altexsoft

APRIL 23, 2019

Any kind of business operates with some amount of data. And these data channels serve as a pair of eyes for executives, supplying them with the analytical information of what is going on with a business and the market. But how to turn unstructured data chunks into something useful? Data warehouse.

Business Intelligence 93

Business Intelligence Analytics Tools Strategy 93

TechCrunch

MAY 16, 2022

Claravine , a self-described marketing data platform, today announced that it raised $16 million in a Series B round led by Five Elms Capital with participation from Grayhawk Capital, Next Frontier Capital, Peninsula Ventures, Kickstart Fund, and Silverton Partners. ” Claravine’s data management platform.

Marketing 182

Marketing Data Software Review Technical Review 182

TechCrunch

APRIL 27, 2021

CEO and founder Ajay Khanna says the company is attempting to marry two technologies that have traditionally lived in silos: business intelligence and artificial intelligence. The first is the business user, who can simply query the data with a natural language question to get results.

Artificial Inteligence 212

Artificial Inteligence Tools Artificial Intelligence Machine Learning 212

CTOvision

SEPTEMBER 12, 2016

The world seems to run on big data nowadays. In fact, it’s sometimes difficult to remember a time when businesses weren’t intensely focused on big data analytics. It’s equally difficult to forget that big data is still relatively new to the mainstream. Rick Delgado.

Big Data 147

Big Data Analytics Data Storage 147

Perficient

FEBRUARY 16, 2023

This is the second blog in a series that explains how organizations can prevent their Data Lake from becoming a Data Swamp, with insights and strategy from Perficient’s Senior Data Strategist and Solutions Architect, Dr. Chuck Brooks.

Data 110

Data Google Cloud Analytics Cloud 110

InnovationM

MAY 14, 2023

Introduction As someone who has hands-on experience in constructing and leveraging data lakes, I can attest to the transformative power these repositories hold for organizations grappling with vast amounts of data. These systems ensure high availability and facilitate the storage of massive data volumes.

Data 52

Data Storage Construction Business Intelligence 52

RapidValue

JUNE 26, 2020

For any organization, be it large or mid-scale, data is important for reviews and predictions and to analyze how effectively the business is running. Apart from generating reports out of daily transactional data, it is equally important that you take a deep dive and analyze the patterns in the historical data.

Analytics 72

Analytics Cloud Technical Review Data 72

Altexsoft

APRIL 16, 2021

Despite the variety and complexity of data stored in the corporate environment, everything is typically recorded in simple columns and rows. This is a classic spreadsheet look we’re all familiar with, and that’s how most databases file data. used for analytical purposes to understand how our business is running.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

Sunflower Lab

OCTOBER 2, 2023

Choosing the Ultimate Data Analytics Tool As a digital service providing enterprise, we constantly find ways to help a business through technology, and with this due process we find new innovative ideas and tools which are yet to be implemented by many of the enterprises in their system.

Azure 40

Azure Analytics UI/UX Software Review 40

Datavail

JULY 27, 2021

Whether you’re a tiny startup or a massive Fortune 500 firm, cloud analytics has become a business best practice. A 2018 survey by MicroStrategy found that 39 percent of organizations are now running their analytics in the cloud, while another 45 percent are using analytics both in the cloud and on-premises.

Azure 98

Azure Analytics Cloud Company 98

Xebia

JANUARY 19, 2023

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. The authors state that the target audience is technical people and, second, business people who work with technical people. Nevertheless, I strongly agree.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

Datavail

JUNE 30, 2022

Organizations of all stripes are increasingly demanding cutting-edge, data-driven business insights—so how can you stay ahead of the curve? As part of an overarching digital transformation strategy, more and more companies are moving their on-premises data analytics into the cloud. Scalability and flexibility.

Analytics 52

Analytics Cloud Business Intelligence Scalability 52

O'Reilly Media - Data

MAY 3, 2018

Privacy-preserving analytics is not only possible, but with GDPR about to come online, it will become necessary to incorporate privacy in your data products. The end result being that there’s even a more heightened awareness around data privacy, and people are acknowledging that problems go beyond a few companies or a few people.

Analytics 127

Analytics Artificial Inteligence Data Machine Learning 127

CIO

JANUARY 12, 2023

Answering these concerns, smart factories are moving to another edge: edge computing, where operational data from Internet of Things (IoT) sensors can be collected and processed for insights in near-real-time. With edge computing, those functions are performed much closer to where the data is created, such as on the factory floor.

Technical Review 189

Technical Review Technology Innovation Data Center 189

Data Virtualization

JANUARY 19, 2023

Reading Time: 2 minutes Today, many businesses are modernizing their on-premises data warehouses or cloud-based data lakes using Microsoft Azure Synapse Analytics. Unfortunately, with data spread.

Azure 52

Azure Architecture Analytics Data 52

CIO

FEBRUARY 13, 2023

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). Cold: On-prem infrastructure As they did in 2022, many IT leaders are reducing investments in data centers and on-prem technologies. “We

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools.

Big Data 78

Big Data Analytics Tools Applications 78

KitelyTech

AUGUST 13, 2023

Working with big data is a challenge that every company needs to overcome to see long-term success in increasingly tough markets. Dealing with big data isn’t just one issue, though. It is dealing with a series of challenges relating to everything from how to acquire data to what to do with data and even data security.

Big Data 52

Big Data Data How To Analytics 52

Coforge

JULY 28, 2021

The Benefits of Integrating SAP Data With Azure Synapse Analytics. The Complications Of Analyzing SAP Data. For modern enterprises in 2021, it’s a challenge to find a cost-efficient, feasible out of box integration with non-SAP data for analytics. Breaking Down Data Silos With Azure Synapse.

Azure 52

Azure Analytics Data Artificial Intelligence 52

Sunflower Lab

OCTOBER 9, 2023

Diving into World of Business Analytics Data analytics is not an old concept, it is an essential practice which has driven business success in the past and the present, it will confidently drive the success in the future too.

Business Analytics 40

Business Analytics Analytics UI/UX Development Team Review 40

Datavail

JULY 7, 2022

The trends are clear: more and more companies are adopting cloud analytics to satisfy their increasing need for cutting-edge business insights. For example, the global cloud analytics market size was $19.04 There are many explanations for why businesses of all sizes and industries are shifting to cloud analytics.

Analytics 52

Analytics Artificial Inteligence Cloud Artificial Intelligence 52

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

AUGUST 13, 2020

Data analytics is one of the key directions for digital transformation in various industries, travel included. And hospitality is no exception: the hotel industry operates large amounts of data by its nature. The sources range from inventory to distribution channels, from customer behavior data to housekeeping records.

Business Intelligence 59

Business Intelligence Hotels Technical Review Technology 59

Datavail

AUGUST 2, 2022

Considering a move to cloud analytics? You’re not alone—and if you’re like many businesses, your IT budget is a major reason why. Before you dive in headfirst, however, it’s important to understand what a cloud analytics migration will mean for your IT expenses. What are the Costs of Cloud Analytics? Analytics compute.

Analytics 52

Analytics Cloud Artificial Inteligence How To 52

CIO

JANUARY 20, 2023

Business intelligence definition Business intelligence (BI) is a set of strategies and technologies enterprises use to analyze business information and transform it into actionable insights that inform strategic and tactical business decisions.

Business Intelligence 348

Business Intelligence Data Business Analytics Analytics 348

Hu's Place - HitachiVantara

JUNE 18, 2019

There has been a growing buzz from analysts and thought leaders on the growing role of object storage in the data center. The All Flash G Series Access node for HCP has unlocked new uses for object storage. He also cites some of the recent enhancement that have been added to HCP.

Storage 66

Storage Software Review Banking Technical Review 66

TIBCO - Connected Intelligence

JULY 13, 2020

While COVID-19 presents a short-term hindrance, I recently simulated this experience with my friend Philip Moston, a business intelligence (BI) Architect and Solutions Consultant at TIBCO partner QuinScape, based in Dortmund, home to the highest concentration of breweries in Germany. . Today, we have over 170 employees.

Analytics 58

Analytics Data Virtualization Business Intelligence 58

Perficient

MARCH 28, 2024

In the world of data warehousing and business intelligence, two key concepts are fundamental: Snowflake and Star Schema. These concepts play a pivotal role in designing effective data models for analyzing large volumes of data efficiently. Star Schema is known for its simplicity and ease of use.

Analytics 52

Analytics Business Intelligence Storage Performance 52

Altexsoft

DECEMBER 9, 2020

In the era of global digital transformation , the role of data analysis in decision-making increases greatly. Still, today, according to Deloitte research, insight-driven companies are fewer than those not using an analytical approach to decision-making, even though the majority agrees on its importance. Stages of analytics maturity.

Analytics 102

Analytics Technical Review Technology Applications 102

Apps Associates

MAY 18, 2021

Background: When data lakes first came on the scene they were usually on-premises Hadoop clusters. Such systems could store any kind of data in its raw format at massive scale. Performing analytics on the data was possible but took a long time and was mostly done in batch (using map reduce routines written in Java).

Cloud 98

Cloud Data Azure Analytics 98