TechCrunch

APRIL 6, 2022

Small- and medium-sized businesses remain the odd ones out, with some data showing that the vast majority haven’t adopted data analytics of any kind. The reasons are myriad, but one major factor is the challenge in managing, transforming and moving the vast amounts of data required for AI and analytics.

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CIO

JUNE 7, 2022

More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. In business analytics, this is the purview of business intelligence (BI). Data analytics and data science are closely related.

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Altexsoft

FEBRUARY 8, 2021

diversity of sales channels, complex structure resulting in siloed data and lack of visibility. These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development.

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TechCrunch

SEPTEMBER 29, 2022

Petrossian met Coalesce’s other co-founder, Satish Jayanthi, at WhereScape, where the two were responsible for solving data warehouse problems for large organizations. (In In computing, a “data warehouse” refers to systems used for reporting and data analysis — analysis usually germane to business intelligence.)

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CIO

NOVEMBER 9, 2022

But experienced data analysts and data scientists can be expensive and difficult to find and retain. Self-service analytics typically involves tools that are easy to use and have basic data analytics capabilities. “We Users have freedom to slice and dice the data without technical know-how,” he says.

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TechCrunch

SEPTEMBER 1, 2022

. “Our thesis was that while companies collect mountains of data, the return on investment on it remains low because it’s predominantly used in dashboards and reporting, not daily actions and automation,” Akmal told TechCrunch in an email interview. These people are in high demand and there aren’t enough to go around.

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TechCrunch

FEBRUARY 24, 2021

There is still a cataloguing and discovery problem though — just because you have all of your data in one place doesn’t mean a data scientist knows what the data represents, who owns it, or what that data might affect in the myriad of web and corporate reporting apps built on top of it. Photo via Select Star.

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CIO

MARCH 27, 2024

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

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TechCrunch

MAY 26, 2022

He’s the founder of Manta , a data lineage platform that automatically scans an organization’s data sources to build a map of data flows. “Data-driven decisions can only be as good as the quality of the underlying data sets and analysis.

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CIO

JANUARY 10, 2023

A related Deloitte tech trends report suggests AI, farther out, will phase out much of the lower-tier tasks associated with IT today. Organizations should plan to brush up on their humanities, as AI technology advances enough to carry out many of the lower-order tasks that IT teams are burdened with today.”

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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%). growth,’’ the firm wrote in a newly-published report on worldwide IT spending in Q4 22. The unified communications market’s meager 1.6%

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Altexsoft

NOVEMBER 28, 2019

But, as a business, you might be interested in extracting value of this information instead of just collecting it. Business intelligence (BI) is a set of technologies and practices to transform business information into actionable reports and visualizations. Who is a business intelligence developer?

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Mentormate

NOVEMBER 29, 2022

Insights are the filtered stream flowing from the pooled data and information. Generating actionable insights from your data is a question of thorough business intelligence and analysis backed by a holistic understanding of your business and organization’s processes. How do you get to Actionable Insights?

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Cloudera

OCTOBER 4, 2023

Ability to handle complex analytic queries — especially when we’re using real-time analytics to augment existing business dashboards and reports with large, complex, long-running business intelligence queries typical for those use cases, and not having the real-time dimension slow these down in any way.

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O'Reilly Media - Ideas

JANUARY 29, 2019

In 2017, we published “ How Companies Are Putting AI to Work Through Deep Learning ,” a report based on a survey we ran aiming to help leaders better understand how organizations are applying AI through deep learning. Data scientists and data engineers are in demand.

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Altexsoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

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Altexsoft

APRIL 16, 2021

As the topic is closely related to business intelligence (BI) and data warehousing (DW), we suggest you to get familiar with general terms first: A guide to business intelligence. An overview of data warehouse types. What is data pipeline. Extract, transform, load or ETL process guide.

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Altexsoft

DECEMBER 9, 2020

Moreover, the MicroStrategy Global Analytics Study reports that access to data is extremely limited, taking 60 percent of employees hours or even days to get the information they need. Hard to believe, but even now there are businesses that do not use technology and manage their operations with pen-and-paper.

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Altexsoft

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. Here’s the video explaining how data engineers work.

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Exadel

AUGUST 26, 2020

Data Analytics for Better Business Intelligence. Data is king in the modern business world. Thanks to technology, collecting data from just about any aspect of a business is possible — including tracking customers’ activity, desires and frustrations while using a product or service.

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InnovationM

MAY 14, 2023

Query engines like Apache Hive and Apache Presto provide SQL-like querying capabilities, enabling users to interactively explore and analyze data stored in the lake. Data Visualization and Business Intelligence: To make sense of the data lake, data visualization, and business intelligence tools play a vital role.

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Agile Engine

DECEMBER 27, 2023

A data analytics consultancy has a team of specialists and engineers who perform data analytics for companies that don’t have the capacity to do it in-house. This type of analytics uses techniques like data aggregation, data mining, and visualization to present data in a way that’s understandable and useful.

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Hacker Earth Developers Blog

JUNE 26, 2019

Apart from that, the recruiter can request a report of all the participating candidates which is directly mailed to the recruiter’s email. . Hiring for data science positions is easier with platforms such as HackerEarth’s developer assessment software. To pull data, candidates should be able to understand Relational Databases.

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Hu's Place - HitachiVantara

JUNE 5, 2019

“ It unleashes data’s ultimate potential by automating the processes that enable the right data to get to the right place at the right time – all while ensuring it remains secure and accessible only to authorized employees. Collaboration was the key as they focused on these four pillars of our data management program.

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Mobilunity

NOVEMBER 24, 2021

The demand for specialists who know how to process and structure data is growing exponentially. In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. Who Is an ETL Engineer? Time-Efficiency.

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Altexsoft

SEPTEMBER 20, 2019

Not only technological companies are concerned about data analysis, but any kind of business is. Analyzing business information to facilitate data-driven decision making is what we call business intelligence or BI. How is data visualized in BI? Business intelligence data processing in a nutshell.

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Altexsoft

FEBRUARY 10, 2021

DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible. It covers the entire data analytics lifecycle, from data extraction to visualization and reporting, using Agile practices to speed up business results.

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O'Reilly Media - Ideas

FEBRUARY 11, 2019

The resource examples I’ll cite will be drawn from the upcoming Strata Data conference in San Francisco , where leading companies and speakers will share their learnings on the topics covered in this post. Data preparation, data governance, and data lineage. Open Data, Data Generation and Data Networks.

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Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. The ELT workflow. ELT vs ETL. Please note!

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ParkMyCloud

MAY 29, 2019

Business Intelligence Analyst. A BI analyst has strong skills in database technology, analytics, and reporting tools and excellent knowledge and understanding of computer science, information systems or engineering. BI Analyst can also be described as BI Developers, BI Managers, and Big Data Engineer or Data Scientist.

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Altexsoft

AUGUST 21, 2019

Dedicated fields of knowledge like data engineering and data science became the gold miners bringing new methods to collect, process, and store data. Using specific tools and practices, businesses implement these methods to generate valuable insights. Data processing in a nutshell and ETL steps outline.

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TIBCO - Connected Intelligence

JUNE 7, 2021

This is a must-read report for any company considering streaming analytics, evaluating top streaming analytics providers against 22 key criteria. According to the report, “TIBCO has strengths in connectors, advanced analytics, development tools, extensibility, usability, and high availability.” Ready for real-time intelligence?

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Altexsoft

OCTOBER 2, 2020

Data integration and interoperability: consolidating data into a single view. Specialist responsible for the area: data architect, data engineer, ETL developer. Without this part, it’s impossible to obtain accurate analytical results and extract valuable business insights. Ensure data accessibility.

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Altexsoft

OCTOBER 29, 2020

Here, we introduce you to ETL testing – checking that the data safely traveled from its source to its destination and guaranteeing its high quality before it enters your Business Intelligence reports. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

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Capgemini

NOVEMBER 14, 2022

Data has to be easy to find, understand, access, and use for everyone in the chain: data engineers, analysts, data scientists, and business users. It makes the data more accessible and understandable to everyone, especially less-skilled data consumers. The next wave of catalog and self service.

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Altexsoft

AUGUST 19, 2022

In our blog, we’ve been talking a lot about the importance of business intelligence (BI), data analytics, and data-driven culture for any company. Users can easily create a wide range of data-intensive, yet intelligible reports and dashboards and share obtained insights. What is Power used for?

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Altexsoft

MARCH 31, 2020

These can be data science teams , data analysts, BI engineers, chief product officers , marketers, or any other specialists that rely on data in their work. The simplest illustration for a data pipeline. Data pipeline components. The final point to which data is transferred is called a destination.

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