Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. Building the right data model is an important part of your data strategy.

Data Modelling 84

Data Modelling Big Data Data Analytics Data Analytics 84

Smart Data Collective

MARCH 29, 2022

In the world of data stacking, which is the theory of data organizing, there are two concepts that center around it: Fact table vs dimension table. This is the topic of harnessing data in a manner that is accessible, and tangible has been posited by many. He explains that “not every business gets value out of their data.

Data Modelling 222

Data Modelling Data Analytics Data Analytics Digital 222

Smart Data Collective

JANUARY 26, 2021

Well, if your company wants to use big data architecture to try to figure out which foreign markets to expand into, that will affect which data sources you’re pulling from. Big Data Analytics News has hailed big data as the future of the translation industry.

Data Architecture 317

Data Architecture Big Data Documentation Monitoring 317

Smart Data Collective

SEPTEMBER 4, 2020

Big data is becoming increasingly important in business decision-making. The market for data analytics applications and solutions is expected to reach $105 billion by 2027. However, big data technology is only a viable tool for business decision-making if it is utilized appropriately.

Big Data 226

Big Data Data Analytics Data Analytics Data Modelling 226

BizAcuity

MARCH 31, 2022

Combined, it has come to a point where data analytics is your safety net first, and business driver second. Predictive Analytics: Predictive analytics is the most talked about topic of the decade in the field of data science. Uncertain economic conditions. Intense competition at every level.

Artificial Intelligence 130

Artificial Intelligence Data Analytics Data Analytics Predictive Analytics 130

Smart Data Collective

NOVEMBER 18, 2020

Data Science is used in different areas of our life and can help companies to deal with the following situations: Using predictive analytics to prevent fraud Using machine learning to streamline marketing practices Using data analytics to create more effective actuarial processes. Where to Use Data Mining?

Data Mining 360

Data Mining Big Data Artificial Intelligence Data Warehouse 360

Sisense

OCTOBER 21, 2020

As a member of the data team, your role is complex and multifaceted, but one important way you support your colleagues across the company is by building and maintaining data models. Picking a direction for your data model. Think like a designer. However, just asking your users, “What do you want?”

Data Modelling 71

Data Modelling Embedded Analytics Design Thinking Big Data 71

Smart Data Collective

APRIL 14, 2021

This is one of the most developed business intelligence tools in the market that comes packed with high-end data analytics and visualization features. This high-end data visualization makes data exploration more accessible to end-users. It comes with embedded dashboards privately and publicly.

Business Intelligence 342

Business Intelligence Business Intelligence Big Data Visualization 342

Insight Software

JANUARY 20, 2021

Organizations that can effectively leverage data as a strategic asset will inevitably build a competitive advantage and outperform their peers over the long term. In order to achieve that, though, business managers must bring order to the chaotic landscape of multiple data sources and data models.

Data Management 95

Data Management Data Analytics Data Analytics E-Commerce 95

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices.

Data Warehouse 235

Data Warehouse Data Quality Data Analytics Data Analytics 235

ElegantJ BI

AUGUST 5, 2020

A Citizen Data Scientist will use his or her domain knowledge and primary skills and experience to gain insight into the data and hypothesize, prototype, analyze and forecast using data to improve accuracy of decisions and to share data and data models with other users.

Data Modelling 130

Data Modelling Data Analytics Data Analytics Monitoring 130

ElegantJ BI

AUGUST 5, 2020

A Citizen Data Scientist will use his or her domain knowledge and primary skills and experience to gain insight into the data and hypothesize, prototype, analyze and forecast using data to improve accuracy of decisions and to share data and data models with other users.

Data Modelling 130

Data Modelling Data Analytics Data Analytics Monitoring 130

ElegantJ BI

AUGUST 5, 2020

A Citizen Data Scientist will use his or her domain knowledge and primary skills and experience to gain insight into the data and hypothesize, prototype, analyze and forecast using data to improve accuracy of decisions and to share data and data models with other users.

Data Modelling 130

Data Modelling Data Analytics Data Analytics Monitoring 130

The BAWorld

SEPTEMBER 27, 2024

And therefore, to figure all this out, data analysts typically use a process known as data modeling. It forms the crucial foundation for turning raw data into actionable insights. Data modeling designs optimal data structures and relationships for storage, access, integrity, and analytics.

Data Modelling 40

Data Modelling IBM Maintenance IBM Support IBM cost 40

Smart Data Collective

JUNE 16, 2022

A data warehouse extracts data from a variety of sources and formats, including text files, excel sheets, multimedia files, and so on. Types: HOLAP stands for Hybrid Online Analytical Processing. This provides both the ROLAP model’s data efficiency and the MOLAP model’s performance.

Data Warehouse 338

Data Warehouse Data Modelling Monitoring Business Intelligence 338

ElegantJ BI

AUGUST 6, 2020

Business intelligence is a body of intelligence gleaned from data and information within your business enterprise. It is comprised of the strategies, data and technologies and brought together for the purpose of data analytics. The Business Intelligence definition today is much different than it was five years ago!

Business Intelligence 130

Business Intelligence Business Intelligence Data Analytics Data Analytics 130

ElegantJ BI

AUGUST 6, 2020

Business intelligence is a body of intelligence gleaned from data and information within your business enterprise. It is comprised of the strategies, data and technologies and brought together for the purpose of data analytics. The Business Intelligence definition today is much different than it was five years ago!

Business Intelligence 130

Business Intelligence Business Intelligence Data Analytics Data Analytics 130

ElegantJ BI

AUGUST 6, 2020

Business intelligence is a body of intelligence gleaned from data and information within your business enterprise. It is comprised of the strategies, data and technologies and brought together for the purpose of data analytics. The Business Intelligence definition today is much different than it was five years ago!

Business Intelligence 130

Business Intelligence Business Intelligence Data Analytics Data Analytics 130

Astera

MAY 30, 2024

What Is Data Analytics? Data analytics is the science of analyzing raw data to draw conclusions about it. The process involves examining extensive data sets to uncover hidden patterns, correlations, and other insights. Data Mining : Sifting through data to find relevant information.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Smart Data Collective

APRIL 2, 2019

These massive storage pools of data are among the most non-traditional methods of data storage around and they came about as companies raced to embrace the trend of Big Data Analytics which was sweeping the world in the early 2010s. The Third Problem – Preparation of Data.

Big Data 215

Big Data Agile Data Analytics Data Analytics 215

Astera

MAY 31, 2024

Data Science vs. Data Analytics Organizations increasingly use data to gain a competitive edge. Two key disciplines have emerged at the forefront of this approach: data science vs data analytics. In contrast, data science enables you to create data-driven algorithms to forecast future outcomes.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

ElegantJ BI

SEPTEMBER 15, 2017

Requirements Planning for Data Analytics Many organizations are so anxious to get into analytics that they fail to consider the depth and breadth of their needs. While it is true that advanced analytics can help every type and size of business, it is important to remember that YOUR organization is not like any other enterprise.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

ElegantJ BI

SEPTEMBER 15, 2017

Requirements Planning for Data Analytics Many organizations are so anxious to get into analytics that they fail to consider the depth and breadth of their needs. While it is true that advanced analytics can help every type and size of business, it is important to remember that YOUR organization is not like any other enterprise.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

ElegantJ BI

SEPTEMBER 15, 2017

Requirements Planning for Data Analytics. Many organizations are so anxious to get into analytics that they fail to consider the depth and breadth of their needs. While it is true that advanced analytics can help every type and size of business, it is important to remember that YOUR organization is not like any other enterprise.

Data Governance 130

Data Governance Data Discovery Government Data Analytics 130

Astera

OCTOBER 7, 2022

The Rise of Unstructured Data Analytics. Until recently, enterprises solely relied on structured data to make business decisions — as conventional software couldn’t ingest, process, and extract the information from unstructured text mainly due to… the lack of structure. Why Is Unstructured Data Analytics Important?

Data Analytics 52

Data Analytics Data Analytics Documentation Customer Experience 52

BizAcuity

JULY 13, 2021

Garnering over more than 6 decades of gaming intelligence experience of our founding team and using advanced technologies like AI & machine learning have a custom-built gaming accelerator platform that provides both visualization and data analytics. Data Enrichment/Data Warehouse Layer. Data Analytics Layer.

Data Warehouse 130

Data Warehouse Artificial Intelligence Data Analytics Data Analytics 130

The Data Administration Newsletter

JULY 21, 2021

There are such huge volumes of data generated in real-time that several businesses don’t know what to do with all of it. Unless big data is converted to actionable insights, there is nothing much an enterprise can do. And outdated data models no longer […].

Big Data 145

Big Data Data Modelling Data Architecture Data Management 145

Insight Software

AUGUST 4, 2023

Providing valuable insights from data that moves the business forward in achieving its strategic objectives is one of the most valuable skills any FP&A or Operational Planning (OP) professional can possess. Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.

Data Analytics 52

Data Analytics Data Analytics Finance Visualization 52

Smart Data Collective

MAY 29, 2023

Skills Sets to Look For When entering into the hiring process for a data analyst there are a few skills that are recommended to look for when narrowing down the pool of options. Data modeling will result in how, in part, a business will set standards.

Big Data 213

Big Data Healthcare Data Modelling Data Analytics 213

Insight Software

MAY 12, 2023

And that’s where data, analytics, and automation tools come in. SAPinsider has an idea for striking the perfect balance between agility and resiliency in supply chain management, and it involves a trio of powerhouse tools: data, analytics, and automation. With Angles, your supply chain future is in safe hands.

Supply Chain 52

Supply Chain Data Analytics Data Analytics Agile 52

Marutitech

MARCH 10, 2022

With the expanding pace of digital changes in business, most analysts are increasingly asking, “What more can we do with data to assist business decisions?” ” Thankfully, there is predictive analytics. Adopting data analytics solutions is a significant milestone in the development and success of any business.

Predictive Analytics 130

Predictive Analytics IBM Maintenance E-Commerce IBM Support 130

Sisense

JANUARY 15, 2021

The modern data team has gained traction in large part thanks to the startups in Silicon Valley that have put an emphasis on collecting, analyzing, and commoditizing data. These younger companies have invested in talent with specific data science skills, particularly with code-driven data analytics.

Skillset 75

Skillset Data Warehouse Data Modelling Business Intelligence 75

Analysts Corner

JUNE 18, 2023

Python, Java, C#) Familiarity with data modeling and data warehousing concepts Understanding of data quality and data governance principles Experience with big data platforms and technologies (e.g., Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Analysts Corner

JULY 28, 2023

IT business analyst as part of the data science team If you are working in this hat, you were (or you will soon) be taking advantage of data analytics in your day job. Companies also call it an IT data analyst or Business Intelligence analyst. You do descriptive, diagnostic, and predictive analysis.

Artificial Intelligence 130

Artificial Intelligence Business Analysis Business Analysis Predictive Analytics 130

Tableau

OCTOBER 8, 2021

Leveraging Looker’s semantic layer will provide Tableau customers with trusted, governed data at every stage of their analytics journey. With its LookML modeling language, Looker provides a unique, modern approach to define governed and reusable data models to build a trusted foundation for analytics.

Government 137

Government Digital Transformation Healthcare Retail 137

The BAWorld

JANUARY 25, 2021

It primarily focuses on developing models that use algorithms to learn and detect patterns, trends, and associations from existing data. Models can apply this learning to new data. Let us have a look at the steps of machine learning followed while building a machine learning model.

Logistics 90

Logistics Data Visualization Artificial Intelligence Visualization 90

Marutitech

DECEMBER 17, 2021

You must be wondering what the different predictive models are? What is predictive data modeling? Which predictive analytics algorithms are most helpful for them? This blog will help you answer these questions and understand the predictive analytics models and algorithms in detail.

Predictive Analytics 140

Predictive Analytics Data Mining Finance Data Analytics 140