FineReport

MARCH 24, 2024

Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis. They identify and interpret trends in complex datasets, optimize statistical results, and maintain databases while devising new data collection processes.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

Sisense

SEPTEMBER 3, 2020

Data scientists usually build models for data-driven decisions asking challenging questions that only complex calculations can try to answer and creating new solutions where necessary. Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Statistics 97

Statistics Metrics Visualization Finance 97

Octopai

MAY 2, 2022

Today, your business users have the same perspective on data analytics. Your dashboards, charts, visualizations… they’re all products. . A successful data analytics team is one that can increase the quantity of data analytics products they develop in a given time while ensuring (and ideally, improving) the level of data quality.

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

Sisense

OCTOBER 15, 2020

Every data professional knows that ensuring data quality is vital to producing usable query results. Streaming data can be extra challenging in this regard, as it tends to be “dirty,” with new fields that are added without warning and frequent mistakes in the data collection process. Step 4: Query.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

datapine

SEPTEMBER 27, 2022

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

Occam's Razor

AUGUST 22, 2011

Slay The Analytics Data Quality Dragon & Win Your HiPPO's Love! Web Data Quality: A 6 Step Process To Evolve Your Mental Model. The Ultimate Web Analytics Data Reconciliation Checklist. The "Action Dashboard" (An Alternative To Crappy Dashboards). Six Data Visualizations That Rock!

KPI 124

KPI Metrics Measurement ROI 124

Smarten

SEPTEMBER 15, 2017

Don’t become a failure statistic! Requirements Planning for Data Analytics. Take the time to develop detailed requirements that consider business user skills, use cases for day-to-day analytics needs and for strategic use, the need for mobile access, scalability, data source integration and other needs.

Analytics 40

Analytics Statistics Data Governance Cost-Benefit 40

DataKitchen

MAY 10, 2021

Data errors impact decision-making. When analytics and dashboards are inaccurate, business leaders may not be able to solve problems and pursue opportunities. Data errors infringe on work-life balance. Data errors also affect careers. You and your data team can accomplish the same thing at your organization.

Testing 214

Testing Manufacturing Data Quality Statistics 214

datapine

DECEMBER 17, 2019

The purpose is not to track every statistic possible, as you risk being drowned in data and losing focus. Using an IT analytics software is extremely useful in the matter: by gathering all your data in a single point-of-truth, you can easily analyze everything at once and create actionable IT dashboards.

Reporting 173

Reporting IT Key Performance Indicator Dashboards 173

Occam's Razor

SEPTEMBER 21, 2015

We send out our multi-tab spreadsheets, our best Google Analytics custom reports , our great dashboards full of data , and more to the tactical layer of data clients. Avoid complex visualizations – they get in the way! Avoid complex visualizations – they get in the way! It is really 88%. : ).

Visualization 160

Visualization Key Performance Indicator Slice and Dice Strategy 160

FineReport

JULY 18, 2022

The features you or your company need are core factors influencing your selection of the data analytics tool. For example, if you want the features of data visualization , such as stunning dashboards and rich charts, business intelligence tools are more suitable for you than a pure programming tool. From FineBI.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

datapine

AUGUST 29, 2022

And with that understanding, you’ll be able to tap into the potential of data analysis to create strategic advantages, exploit your metrics to shape them into stunning business dashboards , and identify new opportunities or at least participate in the process. Your Chance: Want to put your big data knowledge to use?

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Smarten

SEPTEMBER 6, 2019

Self-Serve Data Preparation (SSDP) allows the organization, and its users, to gather, manipulate and analyze complex data from multiple sources in a single interface with easy-to-use tools. SSDP allows business users to leverage tools without the restrictions placed on managed dashboards or standardized reporting tools.

Analytics 51

Analytics IT Business Intelligence Testing 51

Domino Data Lab

JUNE 23, 2019

All you need to know, for now, is that machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to learn based on data by being trained on past examples. ” There’s either incomplete data, missing tracking data or duplicative tracking data, things like that.

Management 110

Management Machine Learning Experimentation Metrics 110

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 1) Data Quality Management (DQM). We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

APRIL 16, 2019

As a direct result, less IT support is required to produce reports, trends, visualizations, and insights that facilitate the data decision making process. From these developments, data science was born (or at least, it evolved in a huge way) – a discipline where hacking skills and statistics meet niche expertise.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

datapine

MAY 17, 2021

Data discovery is a term used to describe the process for collecting data from various sources by detecting patterns and outliers with the help of guided advanced analytics and visual navigation of data, thus enabling consolidation of all business information. 3) Easily work with massive amounts of data.

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161

datapine

DECEMBER 4, 2019

Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company. The accuracy of the predictions depends on the data used to create the model. Graph Analytics.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Andrew White

JANUARY 11, 2021

As such any Data and Analytics strategy needs to incorporate data sovereignty as per of its D&A governance program. Coding skills – SQL, Python or application familiarity – ETL & visualization? What are the new trends around the Data solution architecture (centralized vs de-centralized?).

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

MAY 9, 2024

Data pipelines play a critical role in modern data-driven organizations by enabling the seamless flow and transformation of substantial amounts of data across various systems and apps. For example, streaming data from sensors to an analytics platform where it is processed and visualized immediately.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52