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The 10 Essential SaaS Trends You Should Watch Out For In 2020

datapine

SaaS is a software distribution model that offers a lot of agility and cost-effectiveness for companies, which is why it’s such a reliable option for numerous business models and industries. SaaS Industry is forecasted to reach $55 billion by 2026. Our second forecast for SaaS trends in 2020 is Vertical SaaS. 2) Vertical SaaS.

Software 314
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7 steps for turning shadow IT into a competitive edge

CIO Business Intelligence

After all, 41% of employees acquire, modify, or create technology outside of IT’s visibility , and 52% of respondents to EY’s Global Third-Party Risk Management Survey had an outage — and 38% reported a data breach — caused by third parties over the past two years. There may be times when department-specific data needs and tools are required.

IT 134
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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. The following diagram illustrates the different pipelines to ingest data from various source systems using AWS services.

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How to choose the best AI platform

IBM Big Data Hub

These development platforms support collaboration between data science and engineering teams, which decreases costs by reducing redundant efforts and automating routine tasks, such as data duplication or extraction. Will it be implemented on-premises or hosted using a cloud platform?

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Unleashing Decision Intelligence With Logi Symphony

Jet Global

It requires complex integration technology to seamlessly weave analytics components into the fabric of the host application. Another hurdle is the task of managing diverse data sources, as organizations typically store data in various formats and locations. Full coverage with a plethora of out-of-box data connectors.

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Are You in Control of Your JDE or EBS Data?

Jet Global

Data Quality Challenges for Reporting Teams Poor data quality impacts your team by introducing inaccuracies, inconsistencies, and inefficiencies into their reporting processes. Incomplete, outdated, or erroneous data means your team is generating unreliable insights which can lead to poor decision-making.

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Extreme data center pressure? Burst to the cloud with CDP!

Cloudera

Cloud has given us hope, with public clouds at our disposal we now have virtually infinite resources, but they come at a different cost – using the cloud means we may be creating yet another series of silos, which also creates unmeasurable new risks in security and traceability of our data. A solution. More than likely it is.